DESC:TECHNICAL FIELD
[001] The present disclosure relates to a field of command and control (C2). More particularly, the present invention relates to system and method for real-time state synchronization in multi target tracking/fusion for command and control system.

BACKGROUND
[002] Background description includes information that may be useful in understanding the present invention. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed invention, or that any publication specifically or implicitly referenced is prior art.
[003] Due to the nature of command and control system (include all flavors of C2 systems), the real time availability is of utmost priority along with the accuracy. The surveillance and defence of designated area depends on the deployed Command and Control System. Aim of the command and control systems is to maintain or estimate location, velocities, characteristics and identifications of targets. The combined data makes the situation awareness of designated area by combining the inputs from various sensors and C2 systems. This situation awareness is then provided to different decision support modules or value addition modules for additional knowledge generation which is then presented to operator for their action. The system is developed to be used in C4I systems for defence purposes. Since the defence systems are more prone to enemy attacks, planning of redundancy should be done accordingly. The redundant instances of the system are spread across geographical locations. This ensures location redundancy in the system. The operational efficiency of the system is not hampered even if one of the sites is rendered non-functional.
[004] These real time situation awareness modules run on designated hardware. These hardware are highly efficient and provide uninterrupted power for 24x7 operation. Despite of these provisions, hardware failure and software failure may happen due to various reasons. In such scenario, the military operation performed on system gets interrupted and may leads to fatal situation.
[005] There are some examples of methods proposed in various literatures for state synchronization and redundancy. None of the solution is complete in nature and has practical application for hard real time systems.
[006] The methods proposed in literature work either on strategies of “check-pointing” which require halting the system for some duration or on polling processes where multiple instances of the system are required to work simultaneously to provide output and a polling mechanism is used to select ‘m’ best results out of ‘n’ available instances and combine them to produce output.
[007] For example, the paper “. A Cascading Redundancy Approach for Dependable Real-Time Systems”, by Huseyin Aysan, Radu Dobrin, and Sasikumar Punnekkat, proposes a method of cascading redundancy for state maintenance. The method is suitable only in situations where three of more instances of processes are simultaneously active. The system becomes ineffective in case of single or dual redundancy. Further the method requires calculation of Fault Tolerant (FT)/Fault Aware(FA) feasibility windows for critical, highly-critical and ultra-critical task instances. This is always not feasible.
[008] In the paper titled “A Fault Tolerance Approach for Distributed Systems Using Monitoring Based Replication” by Alexandru Costan, Ciprian Dobre, Florin Pop, Catalin Leordeanu, Valentin Cristea, talks about implementation of optimistic replication protocol using both active and passive strategies. The system requires a server to handle service calls and uses client-server architecture to decide which instance shall reciprocate to the client request. In a high availability, hard real-time system where a large number of sensors are contributing to generate a reliable air situation picture, the proposed client server architecture shall considerably increase the processing overhead.
[009] In another example, the paper titled” Fault Tolerance in Defence C4I Systems” by Sandeep Kumar and Manoj Tyagi, describes the methodologies used in defence C4I systems. These include check pointing mechanisms/restart, recovery blocks and n-version programming. These techniques require temporary halting of system processes for check point and recovery block formation.
[0010] None of the mentioned techniques in above literature talk about system state maintenance and impact of switchover on system state in real time environment. The paper titled “State Restoration in Real-Time Systems” by Lih Chyun Shu and Chang-Ming Tsai, address the problem of state restoration in real time systems by creation of restoration points and taking the snapshot of processes at restoration points. This system works on rollback mechanism where system is reverted to a prior stable state in case of error detection. The method has same limitation as above papers and results in a state which is not real-time depiction of air situation picture and hence not suitable for target tracking environment.
[0011] Real-time fault tolerance and seamless switchover in case of instance failure are required in any target tracking system. All the methods mentioned above provide solution for redundancy and switchover but either the transition procedure renders then non real-time or state synchronization is not achieved. They also suffer from considerable system overload during state synchronization.
[0012] Therefore, there exists a need to provide an improved and efficient mechanism to generate similar estimates so that decision/ calculation on system generated data shall remain same.

OBJECTS OF THE PRESENT DISCLOSURE
[0013] An object of the present disclosure is to provide a system that provides real time, reliable fault tolerance system for multi sensor multi-platform target tracking applications in defenseC4I domain.
[0014] Another object of the present disclosure is to provide a system that provides unique method to synchronize the situation awareness in such a way that it does not put any computational load on the primary instance.
[0015] Another object of the present disclosure is to provide a system that maintains the state with high precision so that decisions and other calculations remain same at other modules utilizing its output.
[0016] Yet another object of the present disclosure is to provide a system that enables heartbeat signal for real-time switchover.
SUMMARY
[0017] The present disclosure relates to a field of command and control (C2). More particularly, the present invention relates to system and method for real-time state synchronization in multi target tracking/fusion for command and control system.
[0018] Since the defence systems are more prone to enemy attacks, planning of redundancy should be done accordingly. The redundant instances of the system are spread across geographical locations. This ensures location redundancy in the system. The operational efficiency of the system is not hampered even if one of the sites is rendered non-functional.
[0019] These real time situation awareness modules run on designated hardware. These hardware are highly efficient and provide uninterrupted power for 24x7 operation. Despite of these provisions, hardware failure and software failure may happen due to various reasons. In such scenario, the military operation performed on system gets interrupted and may leads to fatal situation. To prevent such situations, redundancy of multiple levels is provisioned. The redundancy needs to be made in such a way that full state of situation awareness is maintained and all surveillance and defence operations are not affected during switch over after failure.
[0020] The present invention aims at providing a real time, reliable fault tolerance system for multi sensor multi-platform target tracking applications in defenseC4I domain. The proposed solution uses a unique method to synchronize the situation awareness in such a way that it does not put any computational load on the primary instance which is contributing to the actual system state. It also maintains the state with high precision so that decisions and other calculations remain same at other modules utilizing its output. The method works on state synchronization by utilization readily available state output from primary active instance of the system and the available inputs to the system. Further the system makes use of heartbeat signal for real-time switchover.

BRIEF DESCRIPTION OF THE DRAWINGS
[0021] The accompanying drawings are included to provide a further understanding of the present disclosure, and are incorporated in and constitute a part of this specification. The drawings illustrate exemplary embodiments of the present disclosure and, together with the description, serve to explain the principles of the present disclosure.
[0022] In the figures, similar components and/or features may have the same reference label. Further, various components of the same type may be distinguished by following the reference label with a second label that distinguishes among the similar components. If only the first reference label is used in the specification, the description is applicable to any one of the similar components having the same first reference label irrespective of the second reference label.
[0023] FIG. 1 illustrates an exemplary deployment view of redundant instances of target tracking application, in accordance with an exemplary embodiment of the present disclosure.
[0024] FIG. 2 illustrates an exemplary block diagram for internal processing at secondary active application, in accordance with an exemplary embodiment of the present disclosure.
[0025] FIG. 3 illustrates an exemplary three sensor and three redundant application scenario, in accordance with an exemplary embodiment of the present disclosure.
[0026] FIG. 4 illustrates an exemplary method of working of the labelled speech data collection system, in accordance with an exemplary embodiment of the present disclosure.

DETAILED DESCRIPTION
[0027] The following detailed description is made with reference to the technology disclosed. Preferred implementations are described to illustrate the technology disclosed, not to limit its scope, which is defined by the claims. Those of ordinary skill in the art will recognize a variety of equivalent variations on the description. Various terms as used herein are shown below. To the extent a term used in a claim is not defined below, it should be given the broadest definition persons in the pertinent art have given that term as reflected in printed publications and issued patents at the time of filing.
[0028] The present disclosure relates to a field of command and control (C2). More particularly, the present invention relates to system and method for real-time state synchronization in multi target tracking/fusion for command and control system. Tracking is essential for the guidance, navigation, and control of autonomous systems. A tracking system estimates targets (number of targets and their states) and evaluates the situational environment in an area of interest by taking detections (kinematic parameters and attributes) and tracking these targets with time. The simplest tracking system is a single target tracking (STT) system in a clutterless environment, which assumes one target only in an area of interest. An STT does not require data assignment or association, because the detection of the standalone target can be directly fed to an estimator or filter used to estimate the state of the target. Modern tracking systems usually involve multiple target tracking (MTT) systems, in which one or more sensors generate multiple detections from multiple targets, and one or more tracks are used to estimate the states of these targets. An MTT must assign detections to tracks before the detections can be used to update the tracks.
[0029] FIG. 1 illustrates exemplary block diagram for labelled speech data collection system according to some implementations.
[0030] In an embodiment, the present invention aims at providing a real time, reliable fault tolerance system for multi sensor multi-platform target tracking applications in defenseC4I domain. The proposed solution uses a unique method to synchronize the situation awareness in such a way that it does not put any computational load on the primary instance which is contributing to the actual system state. It also maintains the state with high precision so that decisions and other calculations remain same at other modules utilizing its output. The method works on state synchronization by utilization readily available state output from primary active instance of the system and the available inputs to the system. Further the system makes use of heartbeat signal for real-time switchover.
[0031] FIG. 1 shows an exemplary deployment of redundant instances is shown with two sets hardware (102, 104), the hardware can include general purpose computer, workstation server and the likes based on the load requirements. However, the deployment may include multiple levels of hardware to increase the redundancy level. The actual and real time redundancy can be achieved only if all redundant systems work in active mode i.e., each redundant machine shall process the data as per the active state machine and create its own situation awareness and thereafter synchronize with primary active application.
[0032] In addition to this processing, all secondary active applications also process fused tracks and filter state from primary active instance so that all attribute data (operator fed and system generated data like call sign, type, subtype, identification and any other attribute) and fused track numbers can be transferred to the tracks generated and maintained by secondary active instances.
[0033] Following information (setoff parameters) 106 are transmitted between primary active instance to secondary active instance of applications:
[0034] Fused Tracks: The tracks which are generated by primary active application utilizing the input sensor and system data from various platforms. The fused data also contains the attribute information provided by other modules or operator inputs like call sign, IFF, Type, subtype, identification etc. The fused tracks are basically the situation awareness of designated area.
[0035] Filter State: Each tracking module contains estimation filters (like Kalman, alpha beta, IMM, Particle etc) for generation of final estimate or track fusion. The state of each track is predicted and corrected based on input data and filter used. These filters generate intermediate data and use these data recursively whenever a particular track is being updated. The filter state contains the track wise internal filter parameters. This information is broadcasted from primary active application for synchronizing the estimates at secondary active applications. This process ensures generation similar estimates of fused track at secondary active application.
[0036] Heartbeat and Status: The heartbeat and status information is periodic and provide information about the health status (alive or dead) of application. In case if heartbeat of active application is not received for a fixed duration the next application (as configured or by polling mechanism) becomes active. All other instances start accepting data from that application for further synchronization of situation awareness.
[0037] Sensor/system data: The input data coming from various sensors and systems need to be broadcasted to all applications (primary active and all secondary applications) so that the tracks can be fused at each application. By this mechanism, all secondary active application shall remain in ready state and real time switchover can be achieved.
[0038] Configuration parameters: The configurations parameters applied to primary active application needs to be supplied to all secondary active applications. These configuration parameters may contain information about sensors/systems and user applied configurations. Any difference in configuration shall result in different situation awareness and ultimately result in non-synchronization.
[0039] Accordingly, in an embodiment, a sensor system (100) for tracking an object is provided. The system includes a plurality of electronic devices (102, 104) wherein each of the plurality of electronic devices comprising at least one software application tracking the object and one or more sensors to detect a current state of the at least one application tracking the object. The one or more sensors of each of the plurality of electronic devices configured to generate sensor reports over a window comprised of multiple time scans based on the detected current state.
[0040] The system includes a processor in communication with each of the plurality of electronic devices (102, 104) to assign the at least one software application of a first electronic device (102) selected from the plurality of electronic devices (102, 104) to generate a situation awareness data associated with the object being tracked based on the sensor reports generated by the at least one software application of the first electronic device (102)
[0041] The system also includes a data interface in communication with the processor to broadcast the generated situation awareness data over a network to plurality of electronic devices to avoid redundancy and maintain situation awareness after switch over.
[0042] In an exemplary embodiment, the sensor reports generated by the one or more sensors of each of other plurality of electronic devices are the redundant sensor reports for the sensor reports generated by the at least one software application of the first electronic devices
[0043] In an exemplary embodiment, the sensor system is configured to maintain location data of targets, velocity data of targets, characteristics of targets and identifications of targets.
[0044] In an exemplary embodiment, the object is a designated area of a land.
[0045] In an exemplary embodiment, the generated situation awareness data is used for synchronizing states among each of other plurality of electronic devices.
[0046] In an exemplary embodiment, the sensor reports includes one or more parameters (106) selected from configuration parameters, heart beat from active application, fused tracks from active application and filter state from primary active instance attribute data selected from call sign, identification, type and subtype.
[0047] In an exemplary embodiment, the current state indicative of the at least one software application being in one of an active state or in a passive state.
[0048] In an exemplary embodiment, the present invention eliminates the above mentioned short comings and ensures a seamless real-time fault tolerance by maintaining same system state across multiple redundant instances of the system. The present invention works in Active-Active configuration to achieve real-time redundancy. Among all instances of the application, one instance becomes “Primary Active” and all other redundant instances become “Secondary Active”. The primary active instance of the application processes all the inputs and generates its own situation awareness. The output of the primary active instance is broadcasted for use by all other modules and secondary active application. The Secondary active applications also process input data from sensors/systems to generate their own situation awareness.
[0049] In addition to generation of own situation awareness, the secondary active instance also synchronises the attribute data and generated estimates with primary active instance. The present invention by way of its implementation provides following advantages:
[0050] The system maintains same application state estimated parameters across all instances. It accomplishes this by effectively sharing the system state information of primary instance with all other active secondary instances. The other active instances of the system use the published state information from primary instance to correct their internal states. This insures the decision/solution generated on estimated data remains unique and same across all instances of application ultimately resulting in better utilization of military assets.
[0051] The state sharing mechanism removes the need for methodologies like check-pointing where complete system state is made available to the requesting instance. The current system uses real time state syncing mechanism. Here, the system state is continuously synced by active secondary instances in real time to keep situation awareness similar across instances.
[0052] The system generates situation awareness by combining data from various sensors and other C2 systems. The system provides solution for both sensor and system data redundancy and generates similar state estimates.
[0053] The system works in active-active configuration where one instance becomes primary and rest all instances become secondary. This mechanism eliminates startup delays and ensures the real time switchover. Filter level information sharing mechanism ensures generation precise and similar estimates at every secondary instance.
[0054] The identifiers for system targets (system level track numbers) are independent of internal track numbers used by different instances. All instances of the application process data received from multiple sensors & systems to produce comparable target information. In order to keep system target identifiers similar across all instances, a unique association methodology is developed that provides system level track numbers by taking into consideration track numbers provided by primary instance and sensor contribution matrix.
[0055] The real time state syncing methodology also takes care of difference in system states caused due to network latency. Target reports from different sensors/systems may arrive at different time instances in different packet orders which results in difference of situation awareness across all instances. The real time situation awareness synchronization mechanism takes care of such situations and maintains similar system state across instances.
[0056] FIG. 2 illustrates an exemplary block diagram for internal processing at secondary active application, in accordance with an exemplary embodiment of the present disclosure.
[0057] As shown in FIG. 2, flowing blocks are involved in internal processing at secondary active application.
[0058] Registration (202): Registration is the first step where the tracks from various sensors and systems are converted into common format and their data is brought to a common reference frame. Most sensors provide data in local reference frame and systems provide data in global reference frame. However, this is not limiting to the scope of invention.
[0059] Gating and association (204): After registration, tracks from various sensors/ systems these are subjected to gating and association to identify if they are successor of a fused track or they belong to a newly discovered track from a new target. The plot to track and track to track both type of association is performed at this stage to cater for sensor tracks and system tracks respectively from input. This stage provides the one to one mapping of input track with fused track.
[0060] Association of fused tracks (not provided with reference numeral): The fused tracks received from primary active application are processed and associated with the secondary active application’s tracks. This enables transferring of attribute data from tracks at primary active instance to secondary active instance.
[0061] Track Filtering (206): After association, the position of associated fused track need to be updated and all attribute data (as per system requirements) to be made part of fused track for utilization at system level. For track update various type of filters (Kalman filter, Extended Kalman, Unscented Kalman filter, IMM, Particle Filter etc) are required to estimate updated position based on the previous known data and current input. Apart from the filters, track to track fusion algorithm is used for system track (other C2 systems) fusion. Track shall be updated in primary active application and its filter parameters and track to track fusion parameters are sent to secondary active applications. These filter parameters are used to update the tracks at secondary instance so that the track kinematics and its errors remain similar and shall generate almost similar situation awareness after becoming active.
[0062] Track Maintenance (208): The updated tracks are to be maintained as per user configurations. The amount of time a fused track to remain alive and other user updated attribute data to be updated here. The secondary active instance of the application takes all attribute data from fused tracks provided by active application. The global configuration parameters as applied in primary active application shall be stored in secondary application and applied for track maintenance. Track drop shall be done in secondary application as it is received from primary active application.
[0063] Switching (210): The heartbeat received from primary active application is used to decide if the secondary active application needs to become active. The sequence of becoming active can be predefined or based on any polling mechanism available. Once the application becomes primary active, it starts sending heartbeat with active status to other application and start sending all data to secondary application.
[0064] Data Store (not provided with reference numeral): Global configuration parameters are stored in data store and fetched whenever is required. The data is stored in data structures for faster processing, however the data can be stored in database like sql etc. Updated tracks are also stored here for track maintenance and for association purpose.
[0065] In an exemplary embodiment, the present invention works in active-active configuration i.e. all redundant application process input sensor/system data and create own situation awareness and update attribute data (few examples of attribute data: call sign, identification, type and subtype) from primary active application. To update a track, secondary active application takes filter state from primary active application which ensures the similarity in estimated data. The redundancy can be achieved without using the filter state, however this may lead to difference in estimates which may result in different output from other modules utilizing the output of application for various purpose like decision support, operator assistance, or automation of any military function. Mismatch between the estimated values may be large enough to differ decisions. Such situations shall create a state of confusion while switching over in case of any fault or failure. State of confusion or difference in solution may be fatal in military operations and need to be avoided at any cost.
[0066] To effectively maintain the situation awareness, secondary active instances of application need same input data from sensors/systems, all configuration parameters, heart beat from active application, fused tracks from active application and filter state from primary active instance. Apart from maintaining the attribute data, list of sensors/systems contributing to a fused track is also transferred to secondary instance of application for fusion of tracks and calculating the updated estimate. Since the tracks are fused with statistical methods, the fusion needs to be consistent with primary active application.
[0067] Since estimation or fusion uses some statistical approaches for estimation, the order of processing input has a lot of effect on the results estimated. Consider a scenario where three radars providing input to a system and system contains three applications (one primary active and two secondary active). The data is transmitted through a communication media (Wire or wireless) based on the deployment of system. Due to the uncertainty or order of data, each application may receive data in different order. In such scenario the output of each application shall be different i.e. the estimated values shall be different. The output calculated based on the estimated values at different other modules shall be different. If the switch-over happens at this time, the applied military resources and ongoing military operations may be affected adversely. Such scenarios are dangerous in defence domain and shall lead to catastrophic situation.
[0068] FIG. 3 illustrates an exemplary three sensor and three redundant application scenario (300), in accordance with an exemplary embodiment of the present disclosure. In the scenario depicted in FIG. 3, three sensors providing input to primary and secondary active instances of application. All instances of application are processing input for generation of situation awareness. Primary active gets input in correct order but secondary active 1 and secondary active 2 applications get input in different sequence due to network latency. The situation awareness generated by all three instances will be different at time T1 due to the different input (R1, R2 and R2). At time T2 all applications get input R2, R1 and R3 respectively. After reception of third input at time T3 the situation awareness shall be different due to difference in order of calculation. The scenario is very practical and very frequent in large networks. To avoid such situation a mechanism is required to synchronize the estimation process. The reports are received continuously from sensors in real time and the above scenario my happen at any time. So the one time or periodic check pointing will not work in such situation. The mechanism need to be continuous information sharing so that estimates can be synchronized at each update. The mechanism described here works on continuous and real time information sharing by primary active application and the mechanism to synchronize estimates with primary active at secondary active applications for generation of similar situation awareness.
[0069] Situation Awareness is combination of target’s position, speed, heading, acceleration and various other attribute data. Apart from attribute data, all other data is estimated based on the sensor input. The estimation is done by using statistical method, as explained above the estimated values are directly dependent upon the input values. The estimated values are utilized by other modules for their calculations to aid in decision support and other value additions. In case of the above example, estimated values shall be different due to different sequence of input. Apart from the different sequence, the estimated vales also depend on the number of updates, i.e. if the sequence is same and applications are started at different time the number of input applications have processed will be different. Estimation is a recursive process where output of previous time is taken as input to the current time along with the sensor data. In this case applications started at different time will have different output.
[0070] In both the cases, to get similar situation awareness, synchronization up to the estimation level is required. The state of a target is defined as X; the X vector may contain the position, velocities, acceleration based on the motion model selected. The Kalman filter equations are as follows for time update, i.e. prediction:

Where, ???? is the state estimate of previous time step k and??^?? is the predicted state estimate at time step k. F is the selected motion model. Q is the system error matrix, ????is the estimated covariance matrix at time step k and ?? ^?? is the predicted covariance at time step k. A priory estimate of state and covariance is done based on the motion model F.
[0071] Measurement update equations for Kalman filter,

Where, ???? is the gain calculated based on the predicted covariance of track and covariance of measurement. ???? is the measurement vector received from sensor. Based on equation 4 and 5, the final estimate is calculated based on the gain (K). This gain (K) determines the amount of measurement and prediction to be combined to generate final estimate.
In Multi model filters, there may be more than one filter can be applied in parallel to combine the individual filter estimate. These filters work with various motion models to cater for complex maneuvers of targets. After estimation, each filter output is combined using weights (or probability) calculated based upon their likelihood. Final estimate calculation equations for IMM (Interacting Multiple Model) as are shown below:

Where ???? and ???? are combined state estimates with ‘i’ number of sub filters at time step k. is the weight (probability) of each filter estimate. Sum of all shall be 1.
[0072] As per the equation 3, Kalman gain (K) is calculated at active (primary) application and transferred to secondary application. Apart from filter gain, filter weight (probability) ‘µ’ is also transferred along with updating sensor information as part of filter state. The secondary application shall use this filter state for estimation of new update. The Kalman gain ‘K’ and filter weight (probability) ‘µ’ is calculated in secondary active applications as part of normal filter processing. However, to synchronize with primary active instance, these parameters are discarded and received parameters from primary active instance are used in their place. The above example is provided for Kalman filter and IMM filter but can be applied to all filter used for tracking the target in multi /mono sensor and system environment.
[0073] The system tracks (input C2 fused tracks) provide estimated data along with their covariance values. To estimate fused track using these system tracks is done based on the covariance and their estimates. Weights are calculated based on the covariance and their estimates are combined similar to equation 6. The weights calculated by active application are provided to secondary application along with system estimate information for calculation of combined estimate. Similar to the above processing, the weights are also calculated by secondary active instance but they are discarded and received weights from primary instance are used for parameter estimation and generation of situational awareness. The mechanism to use primary active parameters in secondary active instances ensures the estimation level similarity in situational awareness in real time. This syncing mechanism ensures real time switch over and any ongoing operations/processes are not affected.
[0074] The system targets are identified in the external world by their respective system track numbers. In order to ensure effective switchover among different instances of application, the system track numbers are de-coupled from internal track numbers. Different instances of the application work with local track numbering schemes. Hence track identifiers for a particular track differ among different instances of application. In order to maintain similarity of system track numbers across different instances of application, a track numbering logic is developed which ensures similarity among track numbers across different instances. The responsibility of providing system level track number is designated to primary active instance of application. All the other secondary active instances use the information published by primary instance to provide the track numbers.
[0075] To assign system level track number, the secondary instances of application compare following attributes of their track with published information of active instance:
1. Contributing sensor/system tracks
2. Time difference among tracks
3. Target transmitted attribute data ( if available)
[0076] Along with the above mentioned attribute comparison, gating and vector comparison is done to ensure correct association of tracks while transferring system level track number from primary instance of application to secondary/passive instances. Any other attribute which is available from target on a secure channel can be used for attribute comparison.
[0077] Apart from estimate calculation, other attribute information from active application is transferred to the secondary application track. This information may include identification, type, subtype, call sign, track number etc and other information provided by operator. Attribute transfer and estimate matching ensures the effective situation awareness replication to all secondary application and the solution/decision calculated during switchover shall remain unique and similar. Uniqueness and similarity of generated solution shall ensure the effective utilization of military assets.
[0078] Performance Evaluation:
1. The switch over time from Primary active to secondary active is approximately 100 micro seconds to 1 millisecond which is proportional to the network latency and hardware deployed (Time taken in secondary active triggered as primary active).
2. It is analyzed that the accuracy of state maintenance from primary active to secondary active is 99.2%.
3. The Non kinematic and kinematic parameter maintenance accuracy is approximate 99%.
[0079] The above parameters calculated based on sample data set and depend upon the quality of input data and communication medium. These parameters may further improve if data from accurate sensor/systems used.
[0080] FIG. 4 illustrates an exemplary method of working of the labelled speech data collection system, in accordance with an exemplary embodiment of the present disclosure.
[0081] In an embodiment, a method (400) for tracking an object is provided. The method:
[0082] At step 402, the one or more sensors detects a current state of at least one application configured in each of a plurality of electronic devices (102, 104) for tracking the object. The one or more sensors of each of the plurality of electronic devices configured to generate sensor reports over a window comprised of multiple time scans based on the detected current state.
[0083] At step 404, a processor in communication with each of the plurality of electronic devices assigns the at least one software application of a first electronic device (102) selected from the plurality of electronic devices (102, 104) to generate a situation awareness data associated with the object being tracked based on the sensor reports generated by the at least one software application of the first electronic device (102).
[0084] At step 406, a data interface in communication with the processor broadcast the generated situation awareness data over a network of the plurality of electronic devices to avoid redundancy and maintain situation awareness data after switch over.
[0085] In an exemplary embodiment, the the sensor reports generated by the one or more sensors of each of other plurality of electronic devices are the redundant sensor reports for the sensor reports generated by the at least one software application of the first electronic devices.
[0086] In an exemplary embodiment, the generated situation awareness data is used for synchronizing states among each of other plurality of electronic devices.
[0087] In an exemplary embodiment, a situation awareness across the instances of the system is maintained with high degree of accuracy as syncing is done up to filter state level. This ensures that the estimates produced by different instances are similar.
[0088] a. Difference in system state caused due to network latency is taken care off and similar state is maintained across instances.
[0089] b. Requirement of check pointing is eliminated. The check pointing procedure required halting of system processes for some time duration for synchronizing states among instances.
[0090] The method according to the present invention is free from system halting time and continuous state synchronization is done without affecting the functioning of primary active instance, thereby providing real time availability of all secondary instance all times.
[0091] In an exemplary embodiment, since the system is maintained at active/active configuration, the switch over among different instances is very fast. It does not require system halting time to synchronize among different instances.
[0092] a. Due to similarity in estimates and real-time switchover, the output of modules utilizing the situation awareness for their calculation remains unaffected.
[0093] To summarize, in a multi-sensor target tracking system (C4I system), real time accuracy and availability of target information is of utmost importance. The accuracy of the information is ascertained using no. of filters, fusion techniques and background algorithms. The availability of the information at all times is ensured using multiple levels of redundancy and system state maintenance. In a Multi-Sensor Multi-Target Tracking System multiple sensors continuously contribute to provide target information. The current state of the system is dependent not only on current received data but also on range of data received over time. Hence, if an instance of the system is restarted, in a real time high availability scenario, the system state cannot be replicated by just current instance of data.
[0094] The aim of the present invention is to achieve situation awareness synchronization among multiple instances of the system, so that in case of failure of one instance, the other instance can seamlessly take over functioning of the system without affecting the system state and results calculated on applications output by other modules. There is multiple synchronization methods present in literature like check-pointing, database synchronization, etc. These methods are useful in situation where the system is non real-time. The approaches like check-pointing require temporary halting of system processes till the time check-pointing is done and the instance using check-point is not up. In such a situation loss or real time data occurs which effects the actual state of the system. The real time systems require a mechanism where two instances of the system can be brought to same state without effecting the functioning of each other. The system envisaged here is generic in the sense that it can be utilized in any C4I target tracking system.
[0095] The system uses real-time active/active redundancy and synchronizes the state of targets so that the outputs produced by all the instances of system are identical. The system shall provide for application redundancy and real time takeover in case of instance failure without any change in situation awareness. The proposed methodology eliminates the need for one time complete state synchronization techniques like check pointing. The proposed technique automatically synchronises the situation awareness among instance keeps the states synchronised in real time.
[0096] Further, the approach also takes care of difference in situation awareness caused due to network latency.
[0097] In an exemplary embodiment, the sensor system (100) can include tangible computer-readable media having non-transitory instructions stored thereon/in that are executable by or used to program a server or other computing system (or collection of such servers or computing systems) to perform some of the implementation of processes described herein. For example, computer program code can implement instructions for operating and configuring the system to intercommunicate and to process web pages, applications and other data and media content as described herein. In some implementations, the computer code 26 can be downloadable and stored on a hard disk, but the entire program code, or portions thereof, also can be stored in any other volatile or non-volatile memory medium or device as is well known, such as a ROM or RAM, or provided on any media capable of storing program code, such as any type of rotating media including floppy disks, optical discs, digital versatile disks (DVD), compact disks (CD), microdrives, and magneto-optical disks, and magnetic or optical cards, nano-systems (including molecular memory ICs), or any other type of computer-readable medium or device suitable for storing instructions or data. Additionally, the entire program code, or portions thereof, may be transmitted and downloaded from a software source over a transmission medium, for example, over the Internet, or from another server, as is well known, or transmitted over any other existing network connection as is well known (for example, extranet, VPN, LAN, etc.) using any communication medium and protocols (for example, TCP/IP, HTTP, HTTPS, Ethernet, etc.) as are well known. It will also be appreciated that computer code for the disclosed implementations can be realized in any programming language that can be executed on a server or other computing system such as, for example, C, C++, HTML, any other markup language, Java™, JavaScript, ActiveX, any other scripting language, such as VBScript, and many other programming languages as are well known may be used. (Java™ is a trademark of Sun Microsystems, Inc.).
[0098] In an exemplary embodiment, the sensor system (100) can include may include one or more processors, an input/output (I/O) interface 108, and a memory. Each of the one or more may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, state machines, logic circuitries, and/or any devices that manipulate signals based on operational instructions. Among other capabilities, each of the one or more processors is configured to fetch and execute computer-readable instructions stored in the memory.
[0099] The I/O interface may include a variety of software and hardware interfaces, for example, a web interface, a graphical user interface, and the like. The I/O interface may allow the automated vulnerability scanning and notification apparatus to interact with a user directly or through the client/computing devices. Further, the I/O interface may enable the system 100 or the device 106 to communicate with other computing devices, such as web servers and external data servers. The I/O interface 108 can facilitate multiple communications within a wide variety of networks and protocol types, including wired networks, for example, LAN, cable, etc., and wireless networks, such as WLAN, cellular, or satellite. The I/O interface 108 may include one or more ports for connecting a number of devices to one another or to another server.
[00100] The memory may include any computer-readable medium known in the art including, for example, volatile memory, such as static random access memory (SRAM) and dynamic random access memory (DRAM), and/or non-volatile memory, such as read only memory (ROM), erasable programmable ROM, flash memories, hard disks, optical disks, and magnetic tapes. The memory may include modules, routines, programs, objects, components, data structures, etc., which perform particular tasks or implement particular abstract data types.
[00101] In an embodiment, the sensor system (100) can be implemented in the computer system to enable aspects of the present disclosure. Embodiments of the present disclosure include various steps, which have been described above. A variety of these steps may be performed by hardware components or may be tangibly embodied on a computer-readable storage medium in the form of machine-executable instructions, which may be used to cause a general-purpose or special-purpose processor programmed with instructions to perform these steps. Alternatively, the steps may be performed by a combination of hardware, software, and/or firmware.
[00102] The computer system includes an external storage device, a bus, a main memory, a read only memory, a mass storage device, communication port, and a processor. A person skilled in the art will appreciate that computer system may include more than one processor and communication ports. Examples of processor include, but are not limited to, an Intel® Itanium® or Itanium 2 processor(s), or AMD® Opteron® or Athlon MP® processor(s), Motorola® lines of processors, FortiSOC™ system on a chip processors or other future processors. Processor may include various modules associated with embodiments of the present invention. Communication port can be any of an RS-232 port for use with a modem based dialup connection, a 10/100 Ethernet port, a Gigabit or 10 Gigabit port using copper or fiber, a serial port, a parallel port, or other existing or future ports. Communication port may be chosen depending on a network, such a Local Area Network (LAN), Wide Area Network (WAN), or any network to which computer system connects. Memory can be Random Access Memory (RAM), or any other dynamic storage device commonly known in the art. Read only memory can be any static storage device(s) e.g., but not limited to, a Programmable Read Only Memory (PROM) chips for storing static information e.g., start-up or BIOS instructions for processor. Mass storage may be any current or future mass storage solution, which can be used to store information and/or instructions. Exemplary mass storage solutions include, but are not limited to, Parallel Advanced Technology Attachment (PATA) or Serial Advanced Technology Attachment (SATA) hard disk drives or solid-state drives (internal or external, e.g., having Universal Serial Bus (USB) and/or Firewire interfaces), e.g. those available from Seagate (e.g., the Seagate Barracuda 7200 family) or Hitachi (e.g., the Hitachi Deskstar 7K1000), one or more optical discs, Redundant Array of Independent Disks (RAID) storage, e.g. an array of disks (e.g., SATA arrays), available from various vendors including Dot Hill Systems Corp., LaCie, Nexsan Technologies, Inc. and Enhance Technology, Inc. Bus communicatively couples processor(s) with the other memory, storage and communication blocks. Bus can be, e.g. a Peripheral Component Interconnect (PCI) / PCI Extended (PCI-X) bus, Small Computer System Interface (SCSI), USB or the like, for connecting expansion cards, drives and other subsystems as well as other buses, such a front side bus (FSB), which connects processor to software system. Optionally, operator and administrative interfaces, e.g. a display, keyboard, and a cursor control device, may also be coupled to bus to support direct operator interaction with computer system. Other operator and administrative interfaces can be provided through network connections connected through communication port. External storage device can be any kind of external hard-drives, floppy drives, IOMEGA® Zip Drives, Compact Disc - Read Only Memory (CD-ROM), Compact Disc - Re-Writable (CD-RW), Digital Video Disk - Read Only Memory (DVD-ROM). Components described above are meant only to exemplify various possibilities. In no way should the aforementioned exemplary computer system limit the scope of the present disclosure.
[00103] Although the proposed system has been elaborated as above to include all the main modules, it is completely possible that actual implementations may include only a part of the proposed modules or a combination of those or a division of those into sub-modules in various combinations across multiple devices that can be operatively coupled with each other, including in the cloud. Further the modules can be configured in any sequence to achieve objectives elaborated. Also, it can be appreciated that proposed system can be configured in a computing device or across a plurality of computing devices operatively connected with each other, wherein the computing devices can be any of a computer, a laptop, a smartphone, an Internet enabled mobile device and the like. All such modifications and embodiments are completely within the scope of the present disclosure.
[00104] As used herein, and unless the context dictates otherwise, the term “coupled to” is intended to include both direct coupling (in which two elements that are coupled to each other or in contact each other) and indirect coupling (in which at least one additional element is located between the two elements). Therefore, the terms “coupled to” and “coupled with” are used synonymously. Within the context of this document terms “coupled to” and “coupled with” are also used euphemistically to mean “communicatively coupled with” over a network, where two or more devices are able to exchange data with each other over the network, possibly via one or more intermediary device.
[00105] Moreover, in interpreting both the specification and the claims, all terms should be interpreted in the broadest possible manner consistent with the context. In particular, the terms “comprises” and “comprising” should be interpreted as referring to elements, components, or steps in a non-exclusive manner, indicating that the referenced elements, components, or steps may be present, or utilized, or combined with other elements, components, or steps that are not expressly referenced. Where the specification claims refers to at least one of something selected from the group consisting of A, B, C ….and N, the text should be interpreted as requiring only one element from the group, not A plus N, or B plus N, etc.
[00106] While some embodiments of the present disclosure have been illustrated and described, those are completely exemplary in nature. The disclosure is not limited to the embodiments as elaborated herein only and it would be apparent to those skilled in the art that numerous modifications besides those already described are possible without departing from the inventive concepts herein. All such modifications, changes, variations, substitutions, and equivalents are completely within the scope of the present disclosure. The inventive subject matter, therefore, is not to be restricted except in the protection scope of the appended claims.

ADVANTAGES OF THE PRESENT DISCLOSURE
[00107] The present disclosure provides a system that provides real time, reliable fault tolerance system for multi sensor multi-platform target tracking applications in defenseC4I domain.
[00108] The present disclosure provides a system that provides unique method to synchronize the situation awareness in such a way that it does not put any computational load on the primary instance
[00109] The present disclosure provides a system that maintains the state with high precision so that decisions and other calculations remain same at other modules utilizing its output.
[00110] The present disclosure provides a system that enables heartbeat signal for real-time switchover.
,CLAIMS:1. A sensor system (100) for tracking an object, comprising:
a plurality of electronic devices (102, 104), each of the plurality of electronic devices comprising at least one software application tracking the object and one or more sensors to detect a current state of the at least one application tracking the object, the one or more sensors of each of the plurality of electronic devices configured to generate sensor reports over a window comprised of multiple time scans based on the detected current state;
a processor in communication with each of the plurality of electronic devices (102, 104), the processor configured to assign the at least one software application of a first electronic device (102) selected from the plurality of electronic devices (102, 104) to generate a situation awareness data associated with the object being tracked based on the sensor reports generated by the at least one software application of the first electronic device (102); and
a data interface in communication with the processor, the data interface configured to broadcast the generated situation awareness data over a network to plurality of electronic devices to avoid redundancy and maintain situation awareness after switch over.
2. The sensor system as claimed in claim 1, wherein the sensor reports generated by the one or more sensors of each of other plurality of electronic devices are the redundant sensor reports for the sensor reports generated by the at least one software application of the first electronic devices.
3. The sensor system as claimed in claim 1, wherein the sensor system is configured to maintain location data of targets, velocity data of targets, characteristics of targets and identifications of targets.
4. The sensor system as claimed in claim 1, wherein the object is a designated area of a land.
5. The sensor system as claimed in claim 1, wherein the generated situation awareness data is used for synchronizing states among each of other plurality of electronic devices.
6. The sensor system as claimed in claim 1, wherein the sensor reports includes one or more parameters (106) selected from configuration parameters, heart beat from active application, fused tracks from active application and filter state from primary active instance attribute data selected from call sign, identification, type and subtype.
7. The sensor system as claimed in claim 1, wherein the current state indicative of the at least one software application being in one of an active state or in a passive state.
8. A method (400), performed by a sensor system as claimed in claim 1, for tracking an object, the method comprising:
detecting (402), by one or more sensors, a current state of at least one application configured in each of a plurality of electronic devices (102, 104) for tracking the object, the one or more sensors of each of the plurality of electronic devices configured to generate sensor reports over a window comprised of multiple time scans based on the detected current state;
assigning (404), by a processor in communication with each of the plurality of electronic devices, the at least one software application of a first electronic device (102) selected from the plurality of electronic devices (102, 104) to generate a situation awareness data associated with the object being tracked based on the sensor reports generated by the at least one software application of the first electronic device (102); and
broadcasting (406), through a data interface in communication with the processor, the generated situation awareness data over a network of the plurality of electronic devices to avoid redundancy and maintain situation awareness data after switch over.
9. The method as claimed in claim 8, wherein the sensor reports generated by the one or more sensors of each of other plurality of electronic devices are the redundant sensor reports for the sensor reports generated by the at least one software application of the first electronic devices.
10. The method as claimed in claim 8, wherein the generated situation awareness data is used for synchronizing states among each of other plurality of electronic devices.