DESC:TECHNICAL FIELD
[0001] The present invention relates generally to navigation system and more particularly, to MEMS based navigation system and a method thereof for a wheeled-vehicle.
BACKGROUND
[0002] A navigation system is well known in the art which is an instrument that determines the position of a vehicle. The navigation system uses GPS signals to determine the vehicle's current location and direction.
[0003] The navigation system is required to work in both GPS and GPS-denied environment within the specified accuracy limits. It calls for a hybrid navigation system which can complement GPS data in GPS outage scenario. In recent times, lot of experimental researches are done in the field of navigation for different platforms and scenarios. But every other research has their own limitations and constraints in terms of size, stability, accuracy, compatibility, etc. The main challenge and complexity involved in this technology is to achieve the very high navigational accuracy with low cost MEMS based navigational sensors which are not as accurate as conventional sensors such as FOGs and RLGs. Calibration of MEMS sensors for bias drifts and scale factor nonlinearity along with calibration of magnetic compass for soft and hard iron effects are the two main conventional methods to achieve good accuracies in MEMS based inertial navigation modules. After implementing these conventional calibration techniques, the positional accuracy achieved is 5% of distance travelled. To further improve the positional accuracy with the same set of sensors, need novel techniques other than the conventional ones.
[0004] One of the prior arts disclose “Internal Measurement and Navigation System and Method Having low Drift MEMs Gyroscopes and Accelerometers Operable in GPS Denied Environments”. This prior art illustrates advancement in the field of Inertial Measurement Unit (IMU) with improved algorithm suite and improved packaging that helps in making IMU more accurate and robust, when used in more demanding and standalone condition. However, the accuracies with respect to distance and time were not discussed. Additionally, an important component like magnetometer and its constraints are not exploited to the greatest advantage, as the magnetometer accuracies in general degrades in the vicinity of any stronger magnetic field other than earth’s magnetic field. It is observed that the embodiment of the invention has mentioned the distortion of earth’s magnetic field and its indication but did not provide the calibration methodology for the same. This imposes challenge during heading - attitude measurement in dynamic scenario as any magnetic object in the vicinity will result in generating error. In this respect, a method to minimize the effect of external dynamic magnetic field and to compensate the internal static magnetic field is necessary.
[0005] Another prior art discloses “Vehicle Compass Compensation”. A compass compensation system for automatically and continuously calibrating an electronic compass for a vehicle. But this prior art lacks in considering some practical system limitations like vehicle size, changing the orientation of vehicle etc.
[0006] Therefore, there is a need in the art with a novel approach for accuracy enhancement of MEMS based vehicle navigation system and a method thereof to solve the abovementioned limitations.
SUMMARY OF THE INVENTION
[0007] An aspect of the present invention is to address at least the above-mentioned problems and/or disadvantages and to provide at least the advantages described below.
[0008] Accordingly, in one aspect of the present invention relates to a MEMS based vehicle navigation system (100), the system comprising: a GNSS (Global Navigation Satellite System) receiver (110) configured to collect satellite data input to compute a location and altitude of a vehicle, a proximity sensor unit (120) configured to determine a displacement information of the vehicle, wherein the displacement information is determined by capturing each revolution of an axle of the vehicle, an AHRS (Attitude and Heading Reference System) module (130) configured to determine a heading information of the vehicle, wherein the heading information is determined by inbuilt extended kalman filter of AHRS using the data received from MEMS sensors, a controller (140) configured to receive information’s from the GNSS (Global Navigation Satellite System) receiver, proximity sensor unit and AHRS (Attitude and Heading Reference System) module and determine the next location of the vehicle and further to configured to decide whether to utilize satellite data for determining the next location or not.
[0009] Another aspect of the present invention relates to a MEMS based vehicle navigation method (600), the method comprising: receiving, by a GNSS (Global Navigation Satellite System) receiver, a satellite data input to compute a location and altitude of a vehicle (610), determining, by a proximity sensor unit, a displacement information of the vehicle, wherein the displacement information is determined by capturing each revolution of an axle of the vehicle (620), determining, by an AHRS (Attitude and Heading Reference System) module, a heading information of the vehicle, wherein the heading information is determined by inbuilt extended kalman filter of AHRS using the data received from MEMS sensors (630), and receiving, by a controller, the information’s from the GNSS (Global Navigation Satellite System) receiver, proximity sensor unit and AHRS (Attitude and Heading Reference System) module and determining the next location of the vehicle and further to configured to decide whether to utilize satellite data for determining the next location or not (640).
[0010] Other aspects, advantages, and salient features of the invention will become apparent to those skilled in the art from the following detailed description, which, taken in conjunction with the annexed drawings, discloses exemplary embodiments of the invention.
BRIEF DESCRIPTION OF ACCOMPANYING DRAWINGS
[0011] The detailed description is described with reference to the accompanying figures. In the figures, the left-most digit(s) of a reference number identifies the figure in which the reference number first appears. The same numbers are used throughout the drawings to reference like features and modules.
[0012] Figure 1 shows a functional block diagram of wheeled vehicle navigation system according to an exemplary implementation of the present invention.
[0013] Figure 2 shows a x-y graph of Hard iron magnetic effect before compensation and after compensation according to an exemplary implementation of the present invention.
[0014] Figure 3 shows a x-y graph of Soft iron magnetic effect before compensation and after compensation according to an exemplary implementation of the present invention.
[0015] Figure 4 shows a mounting location of Proximity sensor and Navigation system according to an exemplary implementation of the present invention.
[0016] Figure 5 shows an example plotting of track for GPS and Dead reckoning scenario and error results for 20.2 Km long stretch where duration of each trip is 60 minutes according to an exemplary implementation of the present invention.
[0017] Figure 6 shows a method for MEMS based vehicle navigation system according to an exemplary implementation of the present invention.
[0018] It should be appreciated by those skilled in the art that any block diagrams herein represent conceptual views of illustrative methods embodying the principles of the present disclosure. Similarly, it will be appreciated that any flow charts, flow diagrams, and the like represent various processes which may be substantially represented in computer readable medium and so executed by a computer or processor, whether or not such computer or processor is explicitly shown.

DETAILED DESCRIPTION
[0019] The following description with reference to the accompanying drawings is provided to assist in a comprehensive understanding of exemplary embodiments of the invention as defined by the claims and their equivalents. It includes various specific details to assist in that understanding but these are to be regarded as merely exemplary. Accordingly, those of ordinary skill in the art will recognize that various changes and modifications of the embodiments described herein can be made without departing from the scope and spirit of the invention. In addition, descriptions of well-known functions and constructions are omitted for clarity and conciseness.
[0020] The terms and words used in the following description and claims are not limited to the bibliographical meanings, but, are merely used by the inventor to enable a clear and consistent understanding of the invention. Accordingly, it should be apparent to those skilled in the art that the following description of exemplary embodiments of the present invention are provided for illustration purpose only and not for the purpose of limiting the invention as defined by the appended claims and their equivalents.
[0021] It is to be understood that the singular forms “a,” “an,” and “the” include plural referents unless the context clearly dictates otherwise. Thus, for example, reference to “a component surface” includes reference to one or more of such surfaces.
[0022] By the term “substantially” it is meant that the recited characteristic, parameter, or value need not be achieved exactly, but that deviations or variations, including for example, tolerances, measurement error, measurement accuracy limitations and other factors known to those of skill in the art, may occur in amounts that do not preclude the effect the characteristic was intended to provide.
[0023] Figures discussed below, and the various embodiments used to describe the principles of the present disclosure in this patent document are by way of illustration only and should not be construed in any way that would limit the scope of the disclosure/invention. Those skilled in the art will understand that the principles of the present disclosure/invention may be implemented in any suitably arranged communications system. The terms used to describe various embodiments are exemplary. It should be understood that these are provided to merely aid the understanding of the description, and that their use and definitions in no way limit the scope of the invention. Terms first, second, and the like are used to differentiate between objects having the same terminology and are in no way intended to represent a chronological order, unless where explicitly stated otherwise. A set is defined as a non-empty set including at least one element.
[0024] In the following description, for purpose of explanation, specific details are set forth in order to provide an understanding of the present disclosure. It will be apparent, however, to one skilled in the art that the present disclosure may be practiced without these details. One skilled in the art will recognize that embodiments of the present disclosure, some of which are described below, may be incorporated into a number of systems.
[0025] However, the systems and methods are not limited to the specific embodiments described herein. Further, structures and devices shown in the figures are illustrative of exemplary embodiments of the presently disclosure and are meant to avoid obscuring of the presently disclosure.
[0026] The various embodiments of the present disclosure describe about an accuracy enhancement of MEMS based vehicle navigation system and a method thereof. In the present invention, novel technique to improve the accuracy of both displacement and heading have been implemented, which led to the position accuracy enhancement that brought down the inaccuracies from 5% to 2.5% of distance travelled with the same MEMS navigation system.
[0027] The present invention system ‘Vehicle Navigation System’ is MEMS AHRS/GPS/Proximity sensor integrated navigation system for wheeled vehicles. The most fundamental task of this navigation system is to continuously maintain accurate track of the vehicle’s position in GPS and GPS denied environments. The sensors such as 3-axis MEMS gyros, 3-axis MEMS accelerometer and 3-axis magnetometer and a MEMS pressure sensor as part of Attitude Heading Reference System (AHRS) combines to provide the attitude-heading information input to the embedded Kalman filter. This Kalman filter, in combination with GNSS received NMEA data, provides the 2-dimensional position in uniform and consistent fashion, independent of satellite data availability or magnetic distortion. Barometer in AHRS and altitude information provided by GNSS enhances the system’s capability to provide the 3-dimensional positional data.
[0028] The present invention system and method utilizes i) proximity sensor scale factor calibration for displacement accuracy enhancement ii) module mounting position to minimize the dynamic magnetic field effects, hard and soft iron calibration, dip angle correction for heading accuracy enhancement are implemented and position accuracy (< 2.5% of DT) is achieved from the same MEMS navigation system.
[0029] The navigation is the combination of position and direction of any entity. In mobile scenario, new position of any entity can be found using its initial position, distance travelled and direction of travel. All these activities can easily be done by a satellite based GPS/GNSS receiver, which can provide the positional data efficiently and accurately. But every GPS/GNSS receiver has to encounter GPS/GNSS denied environment that includes thick forest, tunnel, inside building, parking space, spoofing scenario, etc. In this environment, GPS/GNSS receiver will not work at all and give erroneous data to the user. To cope up with this issue, many navigation systems are developed using RLGs, FoGs, HRGs etc., that provide accuracy but are bulky, costly and requires high maintenance and may not be suitable for wheeled vehicle applications with-in reasonable cost. In this context, the present invention focuses on the development of low cost accuracy enhanced Wheeled Vehicle Navigation System as an embedded system, which will work specifically for the wheeled vehicle navigation applications.
[0030] One of the key technologies deployed in the context of present innovation is MEMS technology that is used for finding head, roll, pitch and altitude. During the initial research, it is found that MEMS based sensors are rarely used for vehicle-navigation because of its instability and unreliability during different environmental and mechanical stresses. Additionally, MEMS sensors were not matured enough for long duration application without any other sensor assistance, because of allen variance and bias-instability errors. Apart from this, magnetic compassing is essential in MEMS based navigation solutions to get initial north and magnetic sensors distorts compass measurements, when subjected to unwanted local magnetic fields. However, incorporating MEMs based sensors for navigation drastically reduces the system size, weight, power consumption and cost. Hence, in the present invention calibration is inducted for MEMS sensors to cater bias drifts and scale factor nonlinearity and for magnetic compass to nullify soft and hard iron effects. This mitigates all challenges of MEMS based navigation systems and achieves the position accuracy of the order of 5% of distance travelled.
[0031] In the present invention, novel techniques have been implemented to further improve the position accuracy while using the same low cost and less accurate navigation module. The developed system successfully exhibits <2.5 % of distance travelled accuracy even if GPS outage extends to more than an hour.
[0032] In one embodiment, the position estimation in inertial navigation system is done using displacement and heading information. In the present invention, novel techniques to improve the accuracy of both displacement and heading have been implemented, which led to the position accuracy enhancement that brought down the inaccuracies from 5% to 2.5% of distance travelled with the same MEMS navigation system.
[0033] In one embodiment, the present invention is intended to provide a fully automatic and continuous navigation system for wheeled-vehicle, which continuously generate and send the positional data to users in GPS and GPS-denied environment.
[0034] In one embodiment, the present invention provides a methodology for calculating accurate (error <1.5%) displacement using proximity sensor and bringing positional accuracy (error < 2.5%).
[0035] In one embodiment, the present invention provides a methodology to find the best location on vehicle to mount the navigation system for least dynamic magnetic disturbances. The present invention provides a development of navigation calibration utility to automate the magnetic calibration process. The present invention added a dip-angle correction to get more accurate heading output at different places on earth.
[0036] Figure 1 shows the functional block diagram of wheeled vehicle navigation system according to an exemplary implementation of the present invention.
[0037] The figure shows the functional block diagram of wheeled vehicle navigation system. In the present invention, a wide band GNSS (Global Navigation Satellite System) receiver antenna and proximity sensor is working as input to the system and RS-232/USB data port is used as output from the system. Whereas, GNSS (Global Navigation Satellite System)/GPS (Global Positioning System) receiver, Microcontroller (with Kalman-filtering, Sensor Integration, Magnetic calibration and System Control) and AHRS module (with 3-axis magnetometer, 3-axis gyroscope, 3-axis accelerometer and barometer with extended Kalman filtering for orientation estimation) are inbuilt to the system.
[0038] Wheeled- Vehicle Navigation System Architecture: In the present invention, mainly three subsystems (Fig 1) are used in embodiment of invention: GNSS receiver, AHRS (Attitude and Heading Reference System) module, and Kalman filter engine embedded in ARM based controller. Initially, GNSS board will take satellite data input through wide band antenna to compute the location and altitude of the system. The output of GNSS module will be fed to interface / controller module in the NMEA format. The embedded controller firmware will analyze, decide and compute the next location, based on parameters like previous location, Horizontal Dilution of Precision (HDoP) of GNSS receiver, attitude from AHRS and distance received from standalone odometer.
[0039] The controller will use indigenously developed Kalman filter based logic to decide whether to take satellite data for computing next location or not. If the controller finds the HDoP of the GNSS more than pre-decided threshold value, then it will discard the GNSS data and only take AHRS odometer data to compute the next location. Further, the computed navigation data will be sent to the serial / USB port in the NMEA format for user application for displaying it to the map. In addition to that the vehicle reverse movement sensor is also considered as an input to the navigation system to accurately estimate position in GPS denied scenario. In this regard, the AHRS accelerometer can be utilized to sense the reverse motion for all the vehicles that do not have reverse motion sensor.
[0040] In addition to the NMEA format string, application is developed to create proprietary message string to send through serial / USB port, which is derived from the dead reckoning raw sensor data. The first string includes the information of AHRS output (pitch, roll, pressure and altitude) and second string contains pulse count, odometer count/sec, heading from GPS, heading from AHRS. The positional accuracy of navigation module depends on the displacement information accuracy and heading information accuracy.
[0041] In one embodiment, the present invention relates to a MEMS based vehicle navigation system, the system (100) comprising: a GNSS (Global Navigation Satellite System) receiver (110) configured to collect satellite data input to compute a location and altitude of a vehicle, a proximity sensor unit (120) configured to determine a displacement information of the vehicle, wherein the displacement information is determined by capturing each revolution of an axle of the vehicle, an AHRS (Attitude and Heading Reference System) module (130) configured to determine a heading information of the vehicle, wherein the heading information is determined by inbuilt extended kalman filter of MEMS AHRS using the data received from MEMS sensors such as 3 axes gyroscope, 3 axes accelerometer and 3 axes magnetometer and a controller (140) configured to receive information’s from the GNSS (Global Navigation Satellite System) receiver, proximity sensor unit and AHRS (Attitude and Heading Reference System) module and determine the next location of the vehicle and further to configured to decide whether to utilize satellite data for determining the next location or not.
[0042] The controller further determines the location based on parameters selected from previous location of the vehicle, Horizontal Dilution of Precision (HDoP) of GNSS receiver, displacement information of the vehicle and heading information of the vehicle.
[0043] The controller checks the HDoP (Horizontal Dilution of Precision (HDoP))/Horizontal Dilution of Precision of the GNSS receiver, if HDoP is more than pre-decided threshold value, then the controller discards the satellite data. The HDoP is a measure of the geometric quality of a GPS satellite configuration in the sky. HDoP is a factor in determining the relative accuracy of a horizontal position. The smaller the HDoP number, the better the geometry.
[0044] The position of the vehicle is determined based on head, roll, pitch and pressure measurement from AHRS and displacement measurement from proximity sensor unit. The displacement information of the vehicle and the heading information of the vehicle is determined to compute the location of the vehicle. The displacement information of the vehicle is determined by positioning the proximity sensor unit at a bottom of chassis of the vehicle in proximity to an axle of the vehicle, such that each revolution of the axle is captured efficiently. The proximity sensor unit captures each revolution of the axle as a pulse, and further proximity sensor unit is configured to perform pulse calibration to obtain an accurate number of pulses to find a scale factor which provides precise displacement information.
[0045] The AHRS (Attitude and Heading Reference System) module comprises a tri axis MEMS gyro, tri axis accelerometer, tri axis magnetometer and a MEMS pressure sensor, where the tri axis MEMS gyro captures angular rate measurements in three orthogonal axes, the tri axis accelerometer captures linear acceleration measurements in three orthogonal axes, the tri axis magnetometer captures magnetic field measurements in three orthogonal axes, the MEMS pressure sensor captures altitude/ height/ barometric pressure measurement.
[0046] The MEMS gyro captures angular rate measurements in three orthogonal axes: Measurement of rate of angular movement of vehicle with respect to time in 3-dimensional space. (x, y and z axes), linear acceleration measurements in three orthogonal axes: measurement of rate of change of velocity with respect to time in 3-dimensional space (x, y and z axes). Magnetic field measurements in three orthogonal axes: a magnetic field is a vector field that describes the magnetic influence on an electric charge of other moving charges or magnetized materials. A charge that is moving in a magnetic field experiences a force perpendicular to its own velocity and to the magnetic field. The effects of magnetic fields are commonly seen in permanent magnets, which pull on magnetic materials such as iron, and attract or repel other magnets, creating a torque. Magnetometer captures the magnetic field strength in 3-dimensional space (x, y and z axes).
[0047] The heading information of the vehicle is determined by positioning the AHRS (Attitude and Heading Reference System) module at the bottom of the chassis of the vehicle which is least sensitive place for any dynamic magnetic disturbance in and around the vehicle. The positioning of the AHRS (Attitude and Heading Reference System) module at the bottom of the chassis of the vehicle is determined through conducting the experiment shown in table 1 elaborated in [0060].”
[0048] The controller is further configured to determine a dynamic dip angle correction in magnetic north to obtain true north heading information of the vehicle, where the dip angle is based on the geographical location positional coordinates of the vehicle.
[0049] The system further comprises a vehicle reverse movement sensor, wherein the vehicle reverse movement sensor captures the reverse movement of the vehicle which is an input to the controller to accurately estimate position of the vehicle.
[0050] The novel approaches for accuracy enhancement of both displacement and heading have been implemented in this present invention.
Technique Implemented for Displacement Accuracy Enhancement:
Proximity sensor based displacement measurement:
[0051] The proximity sensor is used to get pulses when the vehicle moves. This sensor is placed on the bottom of chassis in proximity to axle of the vehicle such that every revolution of the axle will be captured efficiently. The benefit of placing the proximity sensor to axle instead of conventional way of placing sensor in proximity to the wheel:
a. No dependency of distance travelled on air-pressure of the tyre.
b. Mounting of sensor on tyre is difficult.
c. Movement of wheel-shock absorbers can affect the sensing of the sensor.
d. During change of vehicle direction one side tyres will revolve more than the other side of the tyres, so error generation may be more for sensor mounted on wheel.
e. Because of location of axle that is generally be on centre of gravity of vehicle, the pulse capture for distance measurement will be measured from the centre of gravity of vehicle.
[0052] After fixing the proximity sensor to the axle, experiment is conducted to find the relation between pulse generated from movement of axle and distance travelled by the vehicle. Further, pulse calibration is done to get accurate number of pulses (<1.5% error) to find the scale factor, i.e. relation between displacement and generated pulses. Pulse calibration involves moving the vehicle in straight line for 100 m. The no. of pulses received for 100 m track is then used to get displacement for the single pulse. The process is repeated many times to get correct scale factor and in turn to get very precise displacement information.
Techniques Implemented for Heading Accuracy Enhancement
[0053] Magnetic Calibration: The presence of high permeable metals will change the magnetic signature of any ferrous object and in-result effect the magnetic compass measurements. These high permeable metals (generally ferrous metal) will generate two types of effect i) Hard iron effect ii) Soft iron effect.
[0054] Figure 2 shows the x-y graph of Hard iron magnetic effect before compensation and after compensation according to an exemplary implementation of the present invention.
[0055] The figure shows the x-y graph of Hard iron magnetic effect before compensation and after compensation. In the hard iron magnetic effect (Figure. 2), the magnetic field remains uniform in the vicinity, but with shifted centre of the magnetic field. As seen in Figure. 2, presence of hard-iron effect shifted the magnetic field centre but the shape of the magnetic field in the vicinity will be seen in circular form.
[0056] Figure 3 shows the x-y graph of Soft iron magnetic effect before compensation and after compensation according to an exemplary implementation of the present invention.
[0057] The figure shows the x-y graph of Soft iron magnetic effect before compensation and after compensation. While, in soft-iron (Figure. 3), magnetic field will not shift its centre but because of the non-uniformity of the field, the x-y magnetic plane will become elliptical in shape. Here, soft-iron presence deforms the uniform magnetic field in circular form to non-uniform elliptical form, without dislocating the centre of the magnetic field.
[0058] Magnetic compensation values can be found from moving the vehicle in circular fashion and logging the data in magnetic calibration utility to find the exact hard-iron and soft-iron compensation required. Once calibrated, the system will work as if no magnetic distortion present inside the vehicle and navigation system will show the results accurately based on how precisely the compensation had been done. In this context, a magnetic field compensation utility is built to ensure that complex magnetic calibration process becomes automated. Hard-iron and soft-iron compensation values are automatically generated during vehicle movement to remove the magnetic distortion error.
Mounting place of Navigation System in the Vehicle by minimizing the effect of dynamic magnetic field:
[0059] As the heading of the system is primarily dependent upon the magnetometer output and hence magnetometer accuracy is of paramount importance. But the magnetometer readings will drift as soon as the AHRS will come into the vicinity of heavy iron object which is having maximum permeability (magnetic property). To reduce the effect of external magnetic field, mounting area is identified on the vehicle through the experiment as tabulated in table 1.
[0060] Effect of dynamic magnetic field: Table 1 shows the effect of dynamic magnetic field on the heading measurement of the system.

Through this experiment, bottom of the chassis is found as the least sensitive place for any dynamic magnetic disturbance in and around the vehicle.
[0061] Figure 4 shows the mounting location of Proximity sensor and Navigation system according to an exemplary implementation of the present invention.
[0062] The figure shows that the proximity sensor is positioned/placed on the bottom of chassis in proximity to axle of the vehicle such that every revolution of the axle will be captured efficiently. Further the AHRS (Attitude and Heading Reference System) module is positioned at the bottom of the chassis of the vehicle which is least sensitive place for any dynamic magnetic disturbance in and around the vehicle. The positioning of the AHRS (Attitude and Heading Reference System) module at the bottom of the chassis of the vehicle is determined through conducting the experiment shown in table 1 elaborated in [0060].”
[0063] Dip Angle Correction: The enhancement in the performance of the system is achieved by dip angle correction in magnetic north to get true north and finally by fine tuning of dead reckoning method steps. A look up table based dip angle correction to get true North is implemented. The look up table is included in the method steps/process where dip angle based on the geographical location positional coordinates (Latitude and longitude) is fed. Thus, dip angle gets corrected dynamically with the changing latitude and longitude information given by the developed navigation system.
[0064] Figure 5 shows an example plotting of track for GPS and Dead reckoning scenario and error results for 20.2 Km long stretch where duration of each trip is 60 minutes according to an exemplary implementation of the present invention.
[0065] The Field trial is done with the developed navigation system mounted on bottom side of chassis of the Gypsy. The vehicle is driven for the track of 20.2 km and the track is plotted on map with only GNSS data. On reaching the starting point, GNSS connection is removed and the last GNSS position is updated with the dead reckoning position, while the vehicle is again driven on the same path. It took one hour to complete the same 20.2 km track and the vehicle’s track with only dead reckoning data is also plotted on the same map.
[0066] The figure 5 shows both the plots i.e. with GNSS position only and with the dead reckoning’s position only. It is found that the amount of error observed between GNSS and without GNSS track is only 1.95% of the distance travelled. Hence, by using aforesaid novel techniques of displacement accuracy improvement and heading accuracy improvement one will able to achieve positional accuracy of less than 2.5%.
[0067] Figure 6 shows a method for MEMS based vehicle navigation system according to an exemplary implementation of the present invention.
[0068] The figure shows a method (600) for MEMS based vehicle navigation system. In one embodiment, the method comprising: receiving, by a GNSS (Global Navigation Satellite System) receiver, a satellite data input to compute a location and altitude of a vehicle (610), determining, by a proximity sensor unit, a displacement information of the vehicle, wherein the displacement information is determined by capturing each revolution of an axle of the vehicle (620), determining, by an AHRS (Attitude and Heading Reference System) module, a heading information of the vehicle, wherein the heading information is determined by inbuilt extended kalman filter of AHRS using the data received from MEMS sensors (630) and receiving, by a controller, the information’s from the GNSS (Global Navigation Satellite System) receiver, proximity sensor unit and AHRS (Attitude and Heading Reference System) module and determining the next location of the vehicle and further to configured to decide whether to utilize satellite data for determining the next location or not (640).
[0069] The method comprises determining the location by the controller, based on parameters selected from previous location of the vehicle, Horizontal Dilution of Precision (HDoP) of GNSS receiver, displacement information of the vehicle and heading information of the vehicle.
[0070] The method comprises discarding the satellite data, by the controller, if the HDoP (Horizontal Dilution of Precision) of the GNSS receiver is more than pre-decided threshold value.
[0071] In case of GNSS Signal unavailability/unreliability, the method comprises determining the position of the vehicle, based on head, roll, pitch and pressure measurement from MEMS AHRS and displacement measurement from odometer.
[0072] The method comprises determining the displacement information of the vehicle and the heading information of the vehicle is to determine/compute the location of the vehicle. The method comprises determining displacement information of the vehicle is by positioning the proximity sensor unit at a bottom of chassis of the vehicle in proximity to an axle of the vehicle, such that each revolution of the axle is captured efficiently. The method comprises determining heading information of the vehicle is by positioning the AHRS (Attitude and Heading Reference System) module at the bottom of the chassis of the vehicle which is least sensitive place for any dynamic magnetic disturbance in and around the vehicle.
[0073] The method further comprising determining a dynamic dip angle correction in magnetic north by the controller, to obtain true north heading information of the vehicle, where the dip angle based on the geographical location positional coordinates of the vehicle.
[0074] In one embodiment, the MEMS AHRS/ GPS/proximity sensor integrated navigation system for wheeled vehicles is disclosed. The MEMS AHRS comprises of tri axis MEMS gyro, tri axis accelerometer, tri axis magnetometer and a MEMS pressure sensor. The system continuously maintains accurate track of the vehicle’s position in GPS and GPS denied environments. The novel techniques, to achieve the accuracy of <2.5% of distance travelled, are implemented.
[0075] In one embodiment, the Nonmagnetic proximity sensor to get displacement information of moving vehicle. The proximity sensor, mounted near the wheel axle, captures the number of rotations of the axle and correlates it to the rotations of the wheel. The displacement is achieved using number of pulses from proximity sensor and the scale factor of the proximity sensor’s pulse.
[0076] In one embodiment, the novel technique to get highly accurate scale factor of proximity sensor where vehicle is moved in straight line. The process is repeated ‘n’ number times at different speeds and averaged out to get very accurate scale factor and in turn to get very precise displacement information (accuracy = 1.5%).
[0077] In one embodiment, the empirical method to get the most suitable place to mount the navigation module on the vehicle on different positions. Based on empirical results in previous steps, chassis of the vehicle is selected as the mounting position for the navigation module so that to get magnetic heading which is not affected by the external environment once calibrated.
[0078] In one embodiment, the development of magnetic field compensation utility to enable the automation of complex magnetic calibration process.
[0079] In one embodiment, the present invention ensures the non-deflected magnetic heading with accuracy of 0.5°. The dynamic dip angle correction to get true north heading is implemented wherein a look up table is included in the method steps where dip angle based on the geographical location positional coordinates is fed based on latitude and longitude information.
[0080] In one embodiment, the accuracy enhancement of displacement and heading accuracy enhancement result in achieving the accuracy enhancement of estimated position of vehicle from 5% of distance travelled to < 2.5% of distance travelled.
[0081] Figures are merely representational and are not drawn to scale. Certain portions thereof may be exaggerated, while others may be minimized. Figures illustrate various embodiments of the invention that can be understood and appropriately carried out by those of ordinary skill in the art.
[0082] In the foregoing detailed description of embodiments of the invention, various features are grouped together in a single embodiment for the purpose of streamlining the disclosure. This method of disclosure is not to be interpreted as reflecting an intention that the claimed embodiments of the invention require more features than are expressly recited in each claim. Rather, as the following claims reflect, inventive subject matter lies in less than all features of a single disclosed embodiment. Thus, the following claims are hereby incorporated into the detailed description of embodiments of the invention, with each claim standing on its own as a separate embodiment.
[0083] It is understood that the above description is intended to be illustrative, and not restrictive. It is intended to cover all alternatives, modifications and equivalents as may be included within the spirit and scope of the invention as defined in the appended claims. Many other embodiments will be apparent to those of skill in the art upon reviewing the above description. The scope of the invention should, therefore, be determined with reference to the appended claims, along with the full scope of equivalents to which such claims are entitled. In the appended claims, the terms “including” and “in which” are used as the plain-English equivalents of the respective terms “comprising” and “wherein,” respectively.

,CLAIMS:

1. A MEMS based vehicle navigation system (100), the system comprising:
a GNSS (Global Navigation Satellite System) receiver (110) configured to collect satellite data input to compute a location and altitude of a vehicle;
a proximity sensor unit (120) configured to determine a displacement information of the vehicle, wherein the displacement information is determined by capturing each revolution of an axle of the vehicle;
an AHRS (Attitude and Heading Reference System) module (130) configured to determine a heading information of the vehicle, wherein the heading information is determined by inbuilt extended kalman filter of AHRS using the data received from MEMS sensors;
a controller (140) configured to receive information’s from the GNSS (Global Navigation Satellite System) receiver, proximity sensor unit and AHRS (Attitude and Heading Reference System) module and determine the next location of the vehicle and further to configured to decide whether to utilize satellite data for determining the next location or not.

2. The system as claimed in claim 1, wherein the Controller determines the location based on parameters selected from previous location of the vehicle, Horizontal Dilution of Precision (HDoP) of GNSS receiver, displacement information of the vehicle and heading information of the vehicle.

3. The system as claimed in claim 1, wherein if the HDoP (Horizontal Dilution of Precision) of the GNSS receiver is more than pre-decided threshold value, then the controller discards the satellite data.

4. The system as claimed in claim 1, wherein the position of the vehicle is determined based on head, roll, pitch and pressure measurement from AHRS and displacement measurement from proximity sensor unit.

5. The system as claimed in claim 1, wherein the displacement information of the vehicle and the heading information of the vehicle is determined to compute the location of the vehicle.

6. The system as claimed in claim 1, wherein the displacement information of the vehicle is determined by positioning the proximity sensor unit at a bottom of chassis of the vehicle in proximity to an axle of the vehicle, such that each revolution of the axle is captured efficiently.

7. The system as claimed in claim 1, wherein the proximity sensor unit captures each revolution of the axle as a pulse, and further proximity sensor unit is configured to perform pulse calibration to obtain an accurate number of pulses to find a scale factor which provides precise displacement information.

8. The system as claimed in claim 1, wherein the AHRS (Attitude and Heading Reference System) module comprises a tri axis MEMS gyro, tri axis accelerometer, tri axis magnetometer and a MEMS pressure sensor, where the tri axis MEMS gyro captures angular rate measurements in three orthogonal axes, the tri axis accelerometer captures linear acceleration measurements in three orthogonal axes, the tri axis magnetometer captures magnetic field measurements in three orthogonal axes, the MEMS pressure sensor captures altitude/ barometric pressure.
9. The system as claimed in claim 1, wherein heading information of the vehicle is determined by positioning the AHRS (Attitude and Heading Reference System) module at the bottom of the chassis of the vehicle which is least sensitive place for any dynamic magnetic disturbance in and around the vehicle.

10. The system as claimed in claim 1, wherein the controller is further configured to determine a dynamic dip angle correction in magnetic north to obtain true north heading information of the vehicle, where the dip angle based on the geographical location positional coordinates of the vehicle.

11. The system as claimed in claim 1, further comprises a vehicle reverse movement sensor, wherein the vehicle reverse movement sensor captures the reverse movement of the vehicle which is an input to the controller to accurately estimate position of the vehicle.

12. A MEMS based vehicle navigation method (600), the method comprising:
receiving, by a GNSS (Global Navigation Satellite System) receiver, a satellite data input to compute a location and altitude of a vehicle (610);
determining, by a proximity sensor unit, a displacement information of the vehicle, wherein the displacement information is determined by capturing each revolution of an axle of the vehicle (620);
determining, by an AHRS (Attitude and Heading Reference System) module, a heading information of the vehicle, wherein the heading information is determined by inbuilt extended kalman filter of AHRS using the data received from MEMS sensors (630); and
receiving, by a controller, the information’s from the GNSS (Global Navigation Satellite System) receiver, proximity sensor unit and AHRS (Attitude and Heading Reference System) module and determining the next location of the vehicle and further to configured to decide whether to utilize satellite data for determining the next location or not (640).

13. The method as claimed in claim 12, wherein determining the location by the controller, based on parameters selected from previous location of the vehicle, Horizontal Dilution of Precision (HDoP) of GNSS receiver, displacement information of the vehicle and heading information of the vehicle.

14. The method as claimed in claim 12, wherein discarding the satellite data, by the controller, if the HDoP (Horizontal Dilution of Precision) of the GNSS receiver is more than pre-decided threshold value.

15. The method as claimed in claim 12, wherein determining the position of the vehicle is based on head, roll, pitch and pressure measurement from AHRS and displacement measurement from proximity sensor unit.

16. The method as claimed in claim 12, wherein the determining/ computing the displacement information of the vehicle and the heading information of the vehicle is to determine/compute the location of the vehicle, where determining displacement information of the vehicle is by positioning the proximity sensor unit at a bottom of chassis of the vehicle in proximity to an axle of the vehicle, such that each revolution of the axle is captured efficiently, where determining heading information of the vehicle is by positioning the AHRS (Attitude and Heading Reference System) module at the bottom of the chassis of the vehicle which is least sensitive place for any dynamic magnetic disturbance in and around the vehicle.

17. The method as claimed in claim 12, further comprising determining a dynamic dip angle correction in magnetic north by the controller, to obtain true north heading information of the vehicle, where the dip angle based on the geographical location positional coordinates of the vehicle.