Description:TECHNICAL FIELD
[0001] The present disclosure relates to the field of sparse microwave imaging. In particular, the present disclosure relates to a system and a method for object detection in a body.

BACKGROUND
[0002] Background description includes information that may be useful in understanding the present disclosure. It is not an admission that any of the information provided herein is prior art or relevant to the presently claimed disclosure, or that any publication specifically or implicitly referenced is prior art.
[0003] Imaging or scanning a body (a 3 dimensional or 3D volume of any shape) to detect the contents of the body has important applications. One such application is to detect concealed objects using application of millimeter-wave (mm-wave) to detect weapons and/or contraband concealed under clothing in close-range.
[0004] For imaging a body using microwave imaging physically the microwave sensors (receivers) are moved to collect responses of the scene to be imaged to electromagnetic signals (waves). Introduction of moving parts not only increases the cost of maintenance but also makes the data collection process slow. When microwave imaging is being used for scrutinizing a large group of people at any security check post, before entering a secure facility or before boarding a public vehicle, delay in each individual scrutiny becomes a bottleneck. For quick, convenient, and safe security inspection a millimeter-wave active imaging systems with fixed antennas (transmitter-cum-receivers) have been used. For generating high resolution images with fixed array, a large number of antenna elements are required. Owing to this the hardware complexity sharply increases, and complex transmission and reception schemes have to be adapted to restrict interference between two separate transmission-reception paths. To reduce the magnitude of the mentioned drawbacks of fixed array imaging, sparse array of sensors has been used that also reduces the acquisition time. The usage of traditional reconstruction algorithms with sparse array of sensors effects the quality of the reconstructed image due to widening of the main lobe, enhancement of the side-lobes, grating lobes, and coherent speckle noise. The requirement of sequential computations is another drawback of the existing techniques.
[0005] Therefore, there is a need for a solution that can image a body for object detection that overcomes the drawback of the existing techniques.

OBJECTS OF THE PRESENT DISCLOSURE
[0006] Some of the objects of the present disclosure, which at least one embodiment herein satisfies are as listed below.
[0007] Principal object of the present disclosure is to provide a system and a method for object detection in a body.
[0008] Another object of the present disclosure is to provide a system and a method for object detection in a body with minimal error, optimum memory requirement, and optimum speed.

SUMMARY
[0009] The present disclosure relates to the field of sparse microwave imaging. In particular, the present disclosure relates to a system and a method for object detection in a body.
[0010] In an aspect, the present disclosure relates to a system for object detection in a body. The system includes one or more transmitters configured as a first planar array to transmit one or more electromagnetic signals towards the body, where the one or more transmitters are communicatively coupled to the system. The system includes one or more receivers configured as a second planar array at one or more 2 dimensional (2D) locations to receive one or more responses associated with the one or more electromagnetic signals from the body, where the one or more receivers are communicatively coupled to the system. The system includes at least one processor and a memory operatively coupled to the at least one processor, where said memory stores executable instructions. When the executable instructions are executed by the at least one processor, the at least one processor performs the following steps. The at least one processor transmits the one or more electromagnetic signals towards the body via the one or more transmitters. The at least one processor receives the one or more responses from the body via the one or more receivers. The at least one processor reconstructs one or more image points using the one or more responses where the one or more image points are associated with one or more physical properties indicating an interaction with the one or more electromagnetic signals at one or more 3 dimensional (3D) locations of the body. The at least one processor detects one or more objects within the body among the one or more image points.
[0011] In an embodiment, the second planar array of the one or more receivers may include one or more occupied sub-arrays and one or more empty sub-arrays, and where each empty sub-array may have at least one occupied sub-array vertically adjacent and at least one occupied sub-array horizontally adjacent.
[0012] In an embodiment, reconstruction of the one or more image points may include the following steps. Estimating, by the at least one processor, the one or more image points using a back-projection technique or a range migration technique, based on the one or more responses. Estimating, by the at least one processor, the one or more responses at the one or more 2D locations in the planar array, using a Stolt interpolation, based on the one or more responses received by the one or more receivers. Building, by the at least one processor, a plurality of vectors to map the one or more 3D image points to the one or more responses at the one or more 2D locations associated with the one or more receivers. Estimating, by the at least one processor, the one or more image points using the one or more responses received via the one or more receivers, the one or more estimated responses and the plurality of vectors.
[0013] In an embodiment, the at least one processor may analyze the responses received by the one or more receivers to estimate the one or more image points using the back-projection technique or the range migration technique independently.
[0014] In an aspect, the present disclosure relates to a method for object detection in a body. The method includes the follow steps. Transmitting, by at least one processor associated with a system, one or more electromagnetic signals towards the body, via one or more transmitters, where the one or more transmitters are configured as a first planar array, and are communicatively coupled to the system. Receiving, by the at least one processor, one or more responses, associated with the one or more electromagnetic signals from the body, via one or more receivers, wherein the one or more receivers are configured as a second planar array at one or more 2 dimensional (2D) locations, and are communicative coupled to the system. Reconstructing, by the at least one processor, one or more image points using the one or more responses, where the one or more image points are associated with one or more physical properties indicating an interaction with the one or more electromagnetic signals at one or more 3D locations of the body. Detecting, by the at least one processor, one or more objects within the body, among the one or more image points.
[0015] In an embodiment, the second planar array of the one or more receivers may include one or more occupied sub-arrays and one or more empty sub-arrays, and where each empty sub-array may have at least one occupied sub-array vertically adjacent and at least one occupied sub-array horizontally adjacent.
[0016] In an embodiment, reconstruction of the one or more image points may include the following steps. Estimating, by the at least one processor, the one or more image points using a back-projection technique or a range migration technique, based on the one or more responses. Estimating, by the at least one processor, the one or more responses at the one or more 2D locations in the planar array, using a Stolt interpolation technique, based on the one or more responses received by the one or more receivers. Building, by the at least one processor, a plurality of vectors to map the one or more 3D image points to the one or more responses at the one or more 2D locations associated with the one or more receivers. Estimating, by the at least one processor, the one or more image points using the one or more responses received via the one or more receivers, the one or more estimated responses and the plurality of vectors.
[0017] In an embodiment, the method may include analyzing, by the at least one processor, the responses received by the one or more receivers to estimate the one or more image points using the back-projection technique or the range migration technique independently.
BRIEF DESCRIPTION OF DRAWINGS
[0018] 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.
[0019] 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.
[0020] FIG. 1 illustrates a flow diagram of the various steps performed by an example system (100) for object detection in a body, in accordance with an embodiment of the current disclosure.
[0021] FIG. 2A illustrates second planar array (200) of receivers with occupied subarrays and empty subarrays in an example system for object detection in a body, in accordance with an embodiment of the present disclosure. FIG. 2B illustrates the 3D image points included in the volume being imaged including planes and grids estimated by an example system for object detection in a body, in accordance to an embodiment of the present disclosure.
[0022] FIG. 3 illustrates an example system (300) similar to the one shown in FIG. 1 for object detection in a body with structural and functional components, in accordance with an embodiment of the present disclosure.
[0023] FIG. 4 illustrates an example method (400) for object detection in a body, in accordance with an embodiment of the present disclosure.

DETAILED DESCRIPTION
[0024] The following is a detailed description of embodiments of the disclosure depicted in the accompanying drawings. The embodiments are in such detail as to clearly communicate the disclosure. However, the amount of detail offered is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the spirit and scope of the present disclosure as defined by the appended claims.
[0025] The ensuing description provides exemplary embodiments only, and is not intended to limit the scope, applicability, or configuration of the disclosure. Rather, the ensuing description of the exemplary embodiments will provide those skilled in the art with an enabling description for implementing an exemplary embodiment. It should be understood that various changes may be made in the function and arrangement of elements without departing from the spirit and scope of the invention as set forth.
[0026] Specific details are given in the following description to provide a thorough understanding of the embodiments. However, it will be understood by one of ordinary skill in the art that the embodiments may be practiced without these specific details. For example, circuits, systems, networks, processes, and other components may be shown as components in block diagram form in order not to obscure the embodiments in unnecessary detail. In other instances, well-known circuits, processes, algorithms, structures, and techniques may be shown without unnecessary detail in order to avoid obscuring the embodiments.
[0027] Also, it is noted that individual embodiments may be described as a process which is depicted as a flowchart, a flow diagram, a data flow diagram, a structure diagram, or a block diagram. Although a flowchart may describe the operations as a sequential process, many of the operations can be performed in parallel or concurrently. In addition, the order of the operations may be re-arranged. A process is terminated when its operations are completed but could have additional steps not included in a figure. A process may correspond to method, a function, a procedure, a subroutine, a subprogram, etc. When a process corresponds to a function, its termination can correspond to a return of the function to the calling function or the main function.
[0028] The word “exemplary” and/or “demonstrative” is used herein to mean serving as an example, instance, or illustration. For the avoidance of doubt, the subject matter disclosed herein is not limited by such examples. In addition, any aspect or design described herein as “exemplary” and/or “demonstrative” is not necessarily to be construed as preferred or advantageous over other aspects or designs, nor is it meant to preclude equivalent exemplary structures and techniques known to those of ordinary skill in the art. Furthermore, to the extent that the terms “includes,” “has,” “contains,” and other similar words are used in either the detailed description or the claims, such terms are intended to be inclusive—in a manner similar to the term “comprising” as an open transition word—without precluding any additional or other elements.
[0029] Reference throughout this specification to “one embodiment” or “an embodiment” or “an instance” or “one instance” means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the present invention. Thus, the appearances of the phrases “in one embodiment” or “in an embodiment” in various places throughout this specification are not necessarily all referring to the same embodiment. Furthermore, the particular features, structures, or characteristics may be combined in any suitable manner in one or more embodiments.
[0030] Various aspects of the present disclosure are described with respect to FIG. 1 to FIG. 4.
[0031] The present disclosure relates to the field of sparse microwave imaging. In particular, the present disclosure relates to a system and a method for object detection in a body.
[0032] In an aspect, the present disclosure relates to a system for object detection in a body. In an exemplary embodiment, the body may be a solid of any shape and size within a prefixed maximum size (volume) and dimensions (height, width and depth) based on the imaging capacity of the system. In an exemplary embodiment, the body may be a human body, an opaque box containing various objects, any specimen with unknown components.
[0033] FIG. 1 illustrates a flow diagram of the various steps performed by an example system (100) for object detection in a body, in accordance with an embodiment of the current disclosure. In an embodiment, the system (100) may include one or more transmitters configured as a first planar array to transmit one or more electromagnetic signals towards the body, where the one or more transmitters are communicatively coupled to the system (100). The system (100) may include one or more receivers configured as a second planar array at one or more 2 dimensional (2D) locations to receive one or more responses associated with the one or more electromagnetic signals from the body, where the one or more receivers are communicatively coupled to the system (100). In an exemplary embodiment, the transmitters and the receivers may be geometrically on the same plane.
[0034] FIG. 2A illustrates second planar array (200) of receivers with occupied subarrays (202) and empty subarrays (204) in an example system (200) for object detection in a body, in accordance with an embodiment of the present disclosure. In an embodiment, the second planar array (200) of the one or more receivers may include of one or more occupied sub-arrays (202) and one or more empty sub-arrays (204), and where each empty sub-array (204) may have at least one occupied sub-array (202) vertically adjacent and at least one occupied sub-array (202) horizontally adjacent as shown in FIG. 2A. In an exemplary embodiment, in the occupied sub-array the receivers are densely packed at a distance of ?/2, where ? is less than the wavelength of the highest frequency in the one or more electromagnetic signals transmitted towards the body. In an exemplary embodiment, the second planar array may have a plurality of occupied subarrays and a plurality of empty subarrays, and each occupied subarray may have a plurality of receivers.
[0035] FIG. 2B illustrates the 3D image points included in the volume (206) being imaged including planes (208) and grids (210) estimated by an example system (100) for object detection in a body, in accordance to an embodiment of the present disclosure. In an exemplary embodiment, the volume (206) that may be imaged for object detection may be divided into equi-spaced planes (208) at fixed distances from the imaging setup including the planar configuration of transmitters and receivers, and each plane (208) may further include grids (210) as shown in FIG. 2B. In an exemplary embodiment, the distance between planes is optimized based on range resolution capacity of the receivers, the number of imaging planes is optimized based on the volume to be imaged, and the volume to be imaged is limited by the field of view of the receivers. In an exemplary embodiment, the system (100) may detect the presence of a target object at the grid points or (3D) image points.
[0036] In an embodiment, referring to FIG. 1 the system (100) may perform the following steps. The system (100) may transmit the one or more electromagnetic signals towards the body via the one or more transmitters. The system (100) may receive the one or more responses from the body via the one or more receivers. In an embodiment, the system (100) may receive the one or more responses at the one or more occupied sub-arrays as shown at step 102. The system (100) may reconstruct one or more image points using the one or more responses where the one or more image points are associated with one or more physical properties indicating an interaction with the one or more electromagnetic signals at one or more 3 dimensional (3D) locations of the body. In an exemplary embodiment, the image points are scatter coefficients at the one or more 3D points.
[0037] In an embodiment, reconstruction of the one or more image points by the system (100) may include the following steps. Estimating, by the system (100), the one or more image points using a back-projection technique or a range migration technique, based on the one or more responses. In an exemplary embodiment, the image points may be estimated using the one or more responses at the one or more occupied subarrays as shown at step 104. In an embodiment, the system (100) may analyze the responses received by the one or more receivers to estimate the one or more image points using the back-projection technique or the range migration technique independently via parallel processing. At step 106, the ranges, the elevation and azimuth angles of image points (target points) are recorded. Reconstruction of the one or more image points by the system (100) may include estimating, by the system (100), the one or more responses at one or more 2D locations in the planar array, using a Stolt interpolation technique, based on the one or more responses received by the one or more receivers as shown at step 108. In an exemplary embodiment, the Stolt interpolation technique may be performed by first converting the data from the spatial domain to the wavenumber domain. In the wavenumber domain, the (response) signal is represented by its spatial and temporal frequencies. Stolt interpolation technique then includes interpolating missing samples by using the known relationship between spatial and temporal frequencies in a moving wavefield. In an exemplary embodiment, Stolt interpolation technique includes conversion of back projection into an angle estimation problem and establishing a continuous relation along every row and along every column of a plane. At step 110, sparse data vectors may be created that include the one or more responses (observations) received by the one or more receivers and the interpolated data. As shown at step 112, reconstruction of the (3D) image points may include building, by the system (100), a plurality of vectors (also referred to as a dictionary matrix) to map the one or more image points to the one or more responses at the one or more 2D locations associated with the one or more receivers. In an exemplary embodiment, each vector in the dictionary matrix represents the Stolt waveform (used in Stolt interpolation) of all the image locations. In an exemplary embodiment, the system (100) may reduce the size (memory required for storage) of this dictionary by only including in the dictionary matrix the parameters for the image locations that were recorded at step 104.
[0038] In an embodiment, reconstruction of the image points may include estimating, by the system (100), the one or more image points (116) using the one or more responses received via the one or more receivers, the one or more estimated responses using the Stolt interpolation technique, and the dictionary matrix (plurality of vectors) by solving a complex optimization problem as shown at step 114. The relation between the observed responses, the dictionary matrix, and the scatter parameter values at the image points is the following:

where, Y is the (sparse) observed responses, A is the dictionary matrix, and X is the scatter coefficient matrix. The complex optimization problem to find the high-resolution 3D image is as given below:

where, is the estimated scatter coefficient matrix which is the 3D image of the body, Y is the observed responses (sparse measured data vector), A is the dictionary matrix, and the second term is associated with Lp norm regularization term.
[0039] In an embodiment, the system (100) detects one or more objects within the body among the one or more image points.
[0040] FIG. 3 illustrates an example system (300) for object detection in a body similar to the system (100) shown in FIG. 1 with structural and functional components, in accordance with an embodiment of the present disclosure. Referring to FIG. 3, the system (100) may include at least one processor (302) that may be implemented as one or more microprocessors, microcomputers, microcontrollers, digital signal processors, central processing units, logic circuitries, and/or any devices that process data based on operational instructions. Among other capabilities, the processor(s) (302) may be configured to fetch and execute computer-readable instructions stored in a memory (304) of the system (100). The memory (304) may be configured to store one or more computer-readable instructions or routines in a non-transitory computer readable storage medium, which may be fetched and executed to create or share data packets over a network service. The memory (304) may comprise any non-transitory storage device including, for example, volatile memory such as random-access memory (RAM), or non-volatile memory such as erasable programmable read only memory (EPROM), flash memory, and the like.
[0041] In an embodiment, the system (100) may include an interface(s) (306). The interface(s) (306) may include a variety of interfaces, for example, interfaces for data input and output devices, referred to as I/O devices, storage devices, and the like. The interface(s) (306) may facilitate communication to/from the system 100. The interface(s) (306) may also provide a communication pathway for one or more components of the system (100). Examples of such components include, but are not limited to, a processing unit/engine(s) (308) and a local database (316). In an embodiment, the local database (316) may be separate from the system (100).
[0042] In an embodiment, the processing engine(s) (308) may be implemented as a combination of hardware and programming (for example, programmable instructions) to implement one or more functionalities of the processing engine(s) (308). In examples described herein, such combinations of hardware and programming may be implemented in several different ways. For example, the programming for the processing engine(s) (308) may be processor-executable instructions stored on a non-transitory machine-readable storage medium and the hardware for the processing engine(s) (308) may comprise a processing resource (for example, one or more processors), to execute such instructions. In the present examples, the machine-readable storage medium may store instructions that, when executed by the processing resource, implement the processing engine(s) (308). In such examples, the system (100) may include the machine-readable storage medium storing the instructions and the processing resource to execute the instructions, or the machine-readable storage medium may be separate but accessible to the system (100) and the processing resource. In other examples, the processing engine(s) (308) may be implemented by electronic circuitry.
[0043] In an embodiment, the processing engine (308) may include a data processing engine (310), a data analysis engine (312), and other modules (316). The processor(s) (302) via the data parameter engine (310) may transmit the one or more electromagnetic signals towards the body via the one or more transmitters. The processor(s) (302) via the data parameter engine (310) may receive the one or more responses from the body via the one or more receivers. The processor(s) (302) via data analysis engine (312) may reconstruct one or more image points using the one or more responses where the one or more image points are associated with one or more physical properties indicating an interaction with the one or more electromagnetic signals at one or more 3 dimensional (3D) locations of the body. The processor(s) (302) via the data analysis engine (312) may detect one or more objects within the body among the one or more image points. The other modules (314) may implement the other functionalities of the system (100).
[0044] In an aspect, the present disclosure relates to a method for object detection in a body. FIG. 4 illustrates an example method (400) for object detection in a body, in accordance with an embodiment of the present disclosure. The system referred to in the method is similar to the system (100) shown in FIG. 1. The method (400) may include the follow steps. At step 402, a system (100) may transmit, one or more electromagnetic signals towards the body, via one or more transmitters, where the one or more transmitters are configured as a first planar array, and are communicatively coupled to the system (100). At step 404, the system (100) may receive one or more responses, associated with the one or more electromagnetic signals from the body, via one or more receivers, where the one or more receivers are configured as a second planar array at one or more 2 dimensional (2D) locations, and are communicative coupled to the system (100). At step 406, the system (100) may reconstruct, one or more image points using the one or more responses, where the one or more image points are associated with one or more physical properties indicating an interaction with the one or more electromagnetic signals at one or more 3D locations of the body. At step 408, the system (100) may detect, one or more objects within the body, among the one or more image points.

ADVANTAGES OF THE PRESENT DISCLOSURE
[0045] The present disclosure provides a system and a method for object detection in a body.
[0046] The present disclosure provides a system and a method for object detection in a body with minimum error, optimum memory requirement, and optimum speed.
, Claims:1. A system (100) for object detection in a body, the system (100) comprising:
one or more transmitters configured as a first planar array to transmit one or more electromagnetic signals towards the body, wherein the one or more transmitters are communicatively coupled to the system;
one or more receivers configured as a second planar array at one or more 2 dimensional (2D) locations to receive one or more responses associated with the one or more electromagnetic signals from the body, wherein the one or more receivers are communicatively coupled to the system;
at least one processor (302); and
a memory (304) operatively coupled to the at least one processor (302), wherein said memory (304) stores executable instructions which when executed by the at least one processor (302), cause the at least one processor (302) to:
transmit, the one or more electromagnetic signals towards the body, via the one or more transmitters;
receive, the one or more responses, from the body, via the one or more receivers;
reconstruct, one or more image points using the one or more responses, wherein the one or more image points are associated with one or more physical properties indicating an interaction with the one or more electromagnetic signals at one or more 3 dimensional (3D) locations of the body; and
detect, one or more objects within the body, among the one or more image points.

2. The system (100) as claimed in claim 1, wherein the second planar array of the one or more receivers comprises of one or more occupied sub-arrays and one or more empty sub-arrays, and wherein each empty sub-array has at least one occupied sub-array vertically adjacent and at least one occupied sub-array horizontally adjacent.
3. The system (100) as claimed in claim 1, wherein reconstruction of the one or more image points comprises:
estimating, by the at least one processor, the one or more image points using a back-projection technique or a range migration technique, based on the one or more responses;
estimating, by the at least one processor, the one or more responses at the one or more 2D locations in the planar array, using a Stolt interpolation technique, based on the one or more responses received by the one or more receivers;
building, by the at least one processor, a plurality of vectors to map the one or more image points to the one or more responses at the one or more 2D locations associated with the one or more receivers; and
estimating, by the at least one processor, the one or more image points using the one or more responses received via the one or more receivers, the one or more estimated responses and the plurality of vectors.

4. The system (100) as claimed in claim 3, wherein the at least one processor analyses the responses received by the one or more receivers to estimate the one or more image points using the back-projection technique or the range migration technique independently.

5. A method (400) for object detection in a body, comprising:
transmitting (402), by at least one processor (302) associated with a system (100), one or more electromagnetic signals towards the body, via one or more transmitters, wherein the one or more transmitters are configured as a first planar array, and are communicatively coupled to the system;
receiving (404), by the at least one processor (302), one or more responses, associated with the one or more electromagnetic signals from the body, via one or more receivers, wherein the one or more receivers are configured as a second planar array at one or more 2 dimensional (2D) locations, and are communicative coupled to the system (100);
reconstructing (406), by the at least one processor (302), one or more image points using the one or more responses, wherein the one or more image points are associated with one or more physical properties indicating an interaction with the one or more electromagnetic signals at one or more 3 dimensional (3D) locations of the body; and
detecting (408), by the at least one processor (302), one or more objects within the body, among the one or more image points.

6. The method (400) as claimed in claim 5, wherein the second planar array of the one or more receivers comprises of one or more occupied sub-arrays and one or more empty sub-arrays, and wherein each empty sub-array has at least one occupied sub-array vertically adjacent and at least one occupied sub-array horizontally adjacent.

7. The method (400) as claimed in claim 1, wherein reconstruction of the one or more image points comprises:
estimating, by the at least one processor (302), the one or more image points using a back-projection technique or a range migration technique, based on the one or more responses;
estimating, by the at least one processor (302), the one or more responses at the one or more 2D locations in the planar array, using a Stolt interpolation technique, based on the one or more responses received by the one or more receivers;
building, by the at least one processor (302), a plurality of vectors to map the one or more image points to the one or more responses at the one or more 2D locations associated with the one or more receivers; and
estimating, by the at least one processor (302), the one or more image points using the one or more responses received via the one or more receivers, the one or more estimated responses and the plurality of vectors.

8. The method (100) as claimed in claim 7 comprising, analyzing, by the at least one processor (302), the responses received by the one or more receivers to estimate the one or more image points using the back-projection technique or the range migration technique independently.