CN113960558A - Non-line-of-sight target positioning method and system based on multi-input multi-output radar - Google Patents
Non-line-of-sight target positioning method and system based on multi-input multi-output radar Download PDFInfo
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Abstract
The invention discloses a non-line-of-sight target positioning method and a system based on a multi-input multi-output radar, and the method comprises the steps of firstly, constructing a multipath signal model and a multipath propagation model of a non-line-of-sight target based on the acquired partial street layout information; preprocessing the collected multi-period radar echoes to generate a range profile; selecting echo data of one period from a range image plane, and performing back projection imaging and similar-back projection imaging algorithm operation on the echo data to generate two images; jointly processing the images generated by the two imaging steps by using an image processing method to obtain candidate targets, and calculating the street width corresponding to each candidate target; extracting the time delay of each path from the distance image plane; and matching candidate targets by taking the path delay as a reference, screening out real targets, and further determining the width of a street. The method solves the problem that the target positioning cannot be carried out when the scene information is incomplete, does not depend on complete scene information, and has the advantages of being suitable for complex positioning scenes, high in robustness and the like.
Description
Technical Field
The invention relates to the technical field of radar shielded target detection, in particular to a non-line-of-sight target positioning method and system based on a multi-input multi-output radar.
Background
The detection of the shielded target is widely applied to the fields of terrorist attacks, urban roadway warfare, disaster rescue, intelligent driving and the like, and mainly comprises two scenes of wall penetration detection and non-line-of-sight detection. The through-wall detection refers to the detection of a shielded object inside a building by using the penetrability of low-frequency electromagnetic waves, and the non-line-of-sight detection refers to the detection of a shielded object on one side of a corner of a block by using the diffraction and reflection propagation of electromagnetic waves.
The diffraction path and the reflection path collected by the radar are called multipath, and the multipath carries target information, so that the detection range can be effectively expanded, and the detection precision is improved, thereby causing extensive research of scholars. These studies achieve target detection, localization and tracking mainly from two aspects, namely a matching method based on multipath separation and an imaging method based on multipath accumulation. The matching method based on the multipath separation is that the multipath is separated and identified based on the difference of information such as time delay or angle of each path, and the target position is determined by a geometric method. The imaging method based on multipath accumulation is used for imaging echoes comprising a plurality of paths, a focusing area is processed by the common image fusion idea, and the method is greatly influenced by environmental noise and has low robustness.
In addition, the two methods both depend heavily on the prior information of the scene, and the algorithm is invalid due to the fact that the scene information is incomplete or inaccurate.
Disclosure of Invention
In view of the above, the present invention provides a method for positioning a non-line-of-sight target based on a mimo radar, which avoids the tedious work of separating and identifying multiple paths, and can effectively solve a multi-target scenario; meanwhile, the image fusion idea is abandoned, and the imaged image is processed by adopting an image combination method, so that the stability is high.
In order to achieve the purpose, the invention provides the following technical scheme:
the invention provides a non-line-of-sight target positioning method based on a multi-input multi-output radar, which comprises the following steps of:
step 1: according to partial street layout information acquired by an operator under the condition of not exposing the position, constructing a multipath signal model and a multipath propagation model of a non-line-of-sight target;
step 2: generating a clear range image plane by preprocessing operations such as windowing, zero padding, pulse compression, cable compensation, average cancellation and the like on the collected multi-period radar echoes;
and step 3: selecting echo data of one period from a range image plane, and performing back projection imaging and similar-back projection imaging algorithm operation on the echo data to generate two images;
and 4, step 4: jointly processing the images generated by the two imaging steps by using an image processing method to obtain candidate targets, and calculating the street width corresponding to each candidate target;
and 5: extracting the time delay of each path from the distance image plane; and matching candidate targets by taking the path delay as a reference, screening out real targets, and determining the width of a street.
Further, the construction process of the two models in the step 1 is as follows:
1.1) constructing a multipath signal model: constructing a corner-shaped street formed by multiple buildings, wherein the corner-shaped street is an 'L' -shaped street, and the 'L' -shaped street is assumed to be composed of Building-1 and Building-2; the operator is approaching the corner C ═ xc,yc]TOne-sided operation radar (i.e. the position of corner C is easy to obtain accurately); target G ═ xG,yG]TIs positioned in the blind area of the radar field of view; let the m-th transmitting antenna and the n-th receiving antenna of the MIMO radar be Tm＝[xm,ym]T，Rn＝[xn,yn]T(ii) a Street width D in the inventionwUnknown, the ordinate of Building-2 was expressed as y for simplification of expressionwRepresents; suppose that the signal transmitted by the m-th transmitting antenna is s (t), and the echo received by the n-th receiving antenna is Zm,n(t) represents;
1.2) constructing a multipath propagation model: because the energy attenuation of the electromagnetic wave is serious after multiple reflections, the invention neglects the contribution of the multi-order reflection path to the target positioning, only considers the diffraction path P1First order reflection path P reflected on Building-12And a first order reflection path P reflected on Building-22Three one-way paths to discuss the object localization process; three single-pass paths with 6 different combinations of round-trip paths, PijRepresenting, 6 paths are stored in vector P:
P＝[P11,P12...Pij,P33]T,i≤j,i,j∈{1,2,3}. (10)
electromagnetic wave follows path PijFrom transmitting antenna TmPropagates to the target G and returns to the receiving antenna RnIs delayed by tauij (m,n)(G)＝τi (m)(G)+τj (n)(G) Is represented by, whereini (m)(G) For transmission time delay, τj (n)(G) Is the receive delay.
Further, a Hamming window with the length of 300 is added in the radar echo in the step 2 to improve the influence caused by frequency spectrum leakage; inverse Fourier transform (IFFT) is a way to realize pulse compression, and zero padding is needed to be carried out on data before IFFT is carried out so as to increase frequency resolution and ensure that radar time domain echoes with high range resolution are obtained after pulse compression; and eliminating static clutter composed of strong reflection of buildings and direct coupling signals between transmitting antennas and receiving antennas by adopting an average cancellation mode.
Further, the two imaging processes in the step 3 specifically include:
3.1) back projection imaging (BP): dividing an imaging area into X multiplied by Y pixel points, wherein any pixel point is defined as p ═ X, Y]TExpressed, the pixel value calculation mode of the pixel point p is as follows:
in the formula, τBP (m)(p) shows electromagnetic waves from the transmitting antenna TmTime delay, tau, of straight line propagation to a pixel point pBP (n)(p) straight-line return to the receiving antenna R from the pixel point pnPropagation delay of (2); repeating the steps until the pixel values of all pixel points in the imaging area are calculated, and using I to form an imageBPRepresents;
3.2) similar-back projection imaging (BP-like): the pixel value calculation mode of the pixel point p is as follows:
wherein the round trip propagation delay tauBP-like (m,n)(p) is calculated by the following expression:
traversing and calculating pixel values of all pixel points in the imaging area to obtain an image IBP-like；
Further, step 4 jointly images the generated two images to generate a candidate target, and the method mainly comprises the following two key parts:
4.1) extracting the centroid of the focusing ghost and the central circle of the focusing ring in the two images: first, for image IBPPerforming a two-dimensional average-constant false alarm detection (CA-CFAR) operation to obtain a sum image IBPThreshold matrix T of equal sizecaAnd then the image I is processed according to the threshold matrixBPSecondly, communicating a focusing region in the binary image by utilizing a bwnable function in MATLAB, calculating the mass center of the communicating region, and stacking the coordinates in a matrix; further, an image I is extracted by utilizing an image processing methodBP-likeThe center circle of the middle focusing ring,stacking it in another matrix;
4.2) obtaining candidate targets based on the centroid matrix and the central circle matrix: two matrixes are distributed in the same imaging area according to positions and are based on an image IBPMiddle-to-first order reflection path P22Generated ghost G22And image IBP-likeMiddle diffraction path P11Generating a plurality of candidate targets G by jointly processing the centroid matrix and the central circle matrixcan＝[Gcan1,Gcan2,.......,GcanL]T(ii) a Then according to the target G and the ghost G22Calculating each candidate target G according to the position characteristic of the symmetry of Building-1canlThe corresponding street width.
Furthermore, the radar has M × N channels, and only one of the channels needs to be selected for multipath delay extraction and target matching, and the candidate target matching process in step 5 is as follows:
5.1) obtaining each multipath time delay: firstly, extracting echoes in an mxn channel, carrying out one-dimensional average-constant false alarm detection (CA-CFAR) on the echoes to obtain multipath time delay, and stacking the multipath time delay in a time delay matrix T;
5.2) candidate target GcanlMultipath delay calculation of (2): calculating electromagnetic waves along path PijFrom the m-th transmitting antenna to the candidate target GcanlThen returning to the time delay of the nth receiving antenna by taul,ijRepresents; candidate target GcanlThe time delay of propagation along all paths in the path matrix P is:
Tl＝[τl,11,τl,12...τl,ijτl,33]T. (14)
5.3) matching the candidate targets: to evaluate a candidate object GcanlSimilarity with the target G, delay matrix T based on the target G and candidate target GcanlDelay matrix T oflDefine HlAnd ElTwo matching factors to represent the matrices T and T, respectivelylThe number of successful matching of the medium elements and the corresponding matching error;
5.4) target judgment rules: repeat 5.2) and 5.3) to calculate GcanThe two factors of all candidate targets in (1) are respectively stored in two matrixes:
H＝[H1,H2...Hl...HL]T, (15)
E＝[E1,E2...El...EL]T. (16)
according to factor HlAnd ElIf the candidate object G is to be foundcanlIf the judgment is the target, matching the factor HlAs the maximum value in the matrix H, error factor ElAnd the minimum value in the matrix E is used for screening out the real target based on the minimum value.
The invention provides a non-line-of-sight target positioning system based on a multi-input multi-output radar, which comprises a memory and a processor, wherein executable codes are stored in the memory, and the processor executes the executable codes to realize the method of any one of claims 1 to 9.
The invention has the beneficial effects that:
the invention provides a non-line-of-sight target positioning method and system based on a multi-input multi-output radar, firstly, a multipath signal model and a multipath propagation model of a typical L-shaped street are constructed according to nearby scene information which is easy to obtain by an operator; secondly, carrying out two different Back Projection (BP) imaging on radar echoes through the propagation characteristics of diffraction and reflection; then, extracting the positions of the focusing areas in the two images by an image processing method, superposing the positions in one image for joint processing, generating a position relation between a ghost image generated by a first-order reflection path in the first image and a focusing ring generated by a diffraction path in the second image, and adding a straight line to enable the focusing areas in the two images to be intersected so as to generate a candidate target; then calculating the multipath propagation delay corresponding to each candidate target, and designing two matching factors to evaluate the similarity between each candidate target and the target; and finally, determining the position of the target and the width of the street according to the target judgment rule.
The invention provides a target positioning method based on a multi-input multi-output radar, which solves the problems that an operator can only rapidly acquire street corner and wall surface information near the radar under the condition of no exposure and is difficult to acquire scene information remotely, namely, the detection of a non-line-of-sight target cannot be accurately carried out when the scene information is partially lost.
Additional advantages, objects, and features of the invention will be set forth in part in the description which follows and in part will become apparent to those having ordinary skill in the art upon examination of the following or may be learned from practice of the invention. The objectives and other advantages of the invention may be realized and attained by the means of the instrumentalities and combinations particularly pointed out hereinafter.
Drawings
In order to make the object, technical scheme and beneficial effect of the invention more clear, the invention provides the following drawings for explanation:
FIG. 1 is a block diagram showing the overall structure of the method of the present invention.
FIG. 2 is a diagram of a multipath propagation model for a typical "L" shaped street.
Fig. 3 is a schematic view of a single-target, dual-target distance image plane.
FIG. 4 is a graph showing the results of a single-target experiment.
Fig. 5 is a schematic diagram of the results of a dual target experiment.
Detailed Description
The present invention is further described with reference to the following drawings and specific examples so that those skilled in the art can better understand the present invention and can practice the present invention, but the examples are not intended to limit the present invention.
Example 1
The general block diagram of the method for locating a non-line-of-sight target based on a multiple-input multiple-output radar provided by the embodiment is shown in fig. 1, and the method comprises the following steps:
step 1: according to partial street layout information acquired by an operator under the condition of not exposing the position, constructing a multipath signal model and a multipath propagation model of a non-line-of-sight target;
step 2: carrying out preprocessing operations such as windowing, zero padding, pulse compression, cable compensation, average cancellation and the like on the collected radar echoes to generate a clear range image plane;
and step 3: selecting echo data of one period from a range image plane, and performing back projection imaging and similar-back projection imaging algorithm operation on the echo data to generate two images;
and 4, step 4: jointly processing the images generated by the two imaging steps by using an image processing method to obtain candidate targets, and calculating the street width corresponding to each candidate target;
and 5: extracting the time delay of each multipath from a range image plane; and (4) performing candidate target matching by taking the multipath time delay as a reference, screening out a real target, and further determining the width of a street.
Preferably, the method comprises the following steps: the step 1 comprises the following steps:
1.1) constructing a multipath signal model:
the corner-shaped street in the embodiment is an L-shaped street, and the L-shaped street is assumed to be composed of Building-1 and Building-2; the operator is approaching the corner C ═ xc,yc]TOne-sided operation radar (i.e. the position of corner C is easy to obtain accurately); target G ═ xG,yG]TIs positioned in the blind area of the radar field of view; let the m-th transmitting antenna and the n-th receiving antenna of the MIMO radar be Tm＝[xm,ym]T，Rn＝[xn,yn]T(ii) a Street width D in the inventionwUnknown, the ordinate of Building-2 was expressed as y for simplification of expressionwAnd (4) showing.
Assuming that the signal transmitted by the mth transmitting antenna is s (t), the echo received by the nth receiving antenna is represented as:
in the formula (8), I and J represent the number of paths of the electromagnetic wave from the transmitting antenna to the target (transmitting path) and from the target to the receiving antenna, respectivelyThe number of paths of a line (reception path); tau isi (m)(G) And τj (n)(G) The propagation time delay of the ith transmitting path and the jth receiving path; sigmai (m)And σj (n)Represents the backscattering coefficient; d (t) represents ambient noise and ξ (t) represents stationary clutter.
1.2) constructing a multipath propagation model: because the energy attenuation of the electromagnetic wave is serious after multiple reflections, the invention neglects the contribution of multi-order reflection paths to the target positioning, only considers 3 single-way paths to discuss the target positioning process (I is J is 3), which are respectively diffraction paths P1Reflected path P reflected on Building-12And a reflected path P reflected on Building-23(ii) a Because the radar echo received by the receiving antenna consists of a transmitting path and a receiving path, 3 single paths have 6 different combinations of round-trip paths, and P is usedijRepresenting, 6 paths are stored in vector P:
P＝[P11,P12...Pij,P33]T,i≤j,i,j∈{1,2,3}, (18)
electromagnetic wave follows path PijFrom transmitting antenna TmPropagates to the target G and returns to the receiving antenna RnIs tau delayed byij (m,n)(G)＝τi (m)(G)+τj (n)(G) In which the transmission is delayed by a time delay taui (m)(G) Can be expressed as:
in the formula (10), | · | represents the distance between two points in English, c represents the speed of electromagnetic wave propagating in air, and G represents22、G33Is represented by a reflected path P2And P2Generating a false object symmetrical about the wall with coordinates:
in a similar manner to that described above,
reception delay tauj (n)(G) Can be expressed as
Preferably, the method comprises the following steps: in the step 2, a Hamming window with the length of 300 is added in the received echo to improve the influence caused by frequency spectrum leakage; inverse Fourier transform (IFFT) is a way to realize pulse compression, and zero padding is needed to be carried out on data before IFFT is carried out so as to increase frequency resolution and ensure that radar time domain echoes with high range resolution are obtained after pulse compression; and eliminating static clutter composed of strong reflection of buildings and direct coupling signals between transmitting antennas and receiving antennas by adopting an average cancellation mode.
Preferably, the method comprises the following steps: the step 3 comprises the following steps:
3.1) back projection imaging (BP): dividing an imaging area into X multiplied by Y pixel points, wherein any pixel point is defined as p ═ X, Y]TRepresents; the pixel value calculation mode of the pixel point p is as follows:
in the formula, τBP (m)(p) shows electromagnetic waves from the transmitting antenna TmTime delay, tau, of straight line propagation to a pixel point pBP (n)(p) return from pixel point p to receiving antenna RnIs expressed as follows:
that is, the pixel value of the pixel point p is equal to the echo amplitude corresponding to the time delay of the electromagnetic wave which is linearly transmitted from the transmitting antenna to the p and then linearly returned to the receiving antenna; repeating the steps until the pixel values of all pixel points in the imaging area are calculated, and using I to form an imageBPRepresents; there are 6 round-trip paths in the radar echoPijI is less than or equal to, i, j belongs to {1,2,3}, and if the path loss does not occur in the actual data acquisition process, 6 focus areas G should exist in the image generated by BP imagingij,i≤,i,j∈{1,2,3}。
3.2) similar-back projection imaging (BP-like): the pixel value calculation mode of the pixel point p is as follows:
wherein the round trip propagation delay tauBP-like (m,n)(p) is calculated by the following expression:
converting the round trip propagation delay from the pixel point p to the transceiving antenna into the round trip delay from the pixel point p to the corner C plus the delay from the transceiving antenna to the corner C; traversing and calculating pixel values of all pixel points in the imaging area to obtain an image IBP-like(ii) a Because the calculation method of the round-trip delay of the pixel point is converted into the method taking the wall corner C as the reference point, under the condition that 6 round-trip paths are successfully collected, the BP-like imaging result is 6 concentric circular rings C taking the wall corner C as the center of a circleij,i≤,i,j∈{1,2,3}；
Image IBPAnd image IBP-likeThe middle focusing areas carry position information of the target, and the position of the target can be determined by jointly processing the focusing areas in the two images; for example, image IBPMiddle round-trip reflection path P22Mapped focus ghost G22And image IBP-likeMiddle round-trip diffraction path P11Mapped to a focusing circle C11The following relationships exist: over-focusing ghost G22The center of the focusing ring is provided with a straight line parallel to the y axis11The intersection point in the non-line-of-sight region is a target position; the difficulty of the above operation is that it cannot be directly taken from the image IBPAnd image IBP-likeIdentifying a focus ghost G in the plurality of focus regions22And a focusing ring C11。
Preferably, the method comprises the following steps: step 4 is based on the ghost by focus G mentioned in step 322And a focusing ring C11The idea of positioning provides a blind processing positioning method, which mainly comprises the following two key parts:
4.1) extracting the centroid of the focusing ghost and the central circle of the focusing ring in the two images: first, for image IBPPerforming two-dimensional average-constant false alarm detection (CA-CFAR) to obtain image IBPThreshold matrix T of equal sizecaAnd then, carrying out binarization on the image according to the following rules:
secondly, communicating the focus areas in the binary image by using a bwlable function in MATLAB, and supposing that Z communicated areas are extracted in total; the centroid of the connected region is then calculated:
in the formula (18), [ x ]z,yz]TZ ∈ {1,2.. Z } represents the centroid of the extracted Z-th connected region, [ x ∈ {1,2.. Z }, wherezq,yzq]TAnd (3) representing the coordinates of the Q-th pixel point in the z-th connected region, wherein Q belongs to {1,2z}，QzRepresenting the number of pixel points contained in the z-th connected region;
due to focusing ghost G22And the radar is positioned in a sight distance area of the radar, so that a communication area meeting the following conditions is screened out:
will all satisfy Ω1Is stacked in a matrix W, W ═ W1,W2...WK]T(K≤Z)；
Further, an image I is extracted by utilizing an image processing methodBP-likeThe central circle of the middle focusing ring is stacked in a matrix V ═ V1,V2...Vu,VU]TIn (1).
4.2) obtaining candidate targets based on the centroid W matrix and the central circle matrix V: distributing the matrix W and the matrix V in the same imaging area according to positions, making K straight lines parallel to the y axis through K centroids in the matrix W to enable the straight lines to be intersected with U circles in the matrix V, taking the obtained intersection points as candidate targets, and uniformly using [ x ] as a targetcan,ycan]TRepresents; because the target is positioned above the non-line-of-sight area and Building-2 of the radar, the candidate target is preliminarily screened on the basis that:
Ω3:{ycan≥yc}, (30)
will satisfy omega simultaneously2And Ω3Vector G for candidate targetcan＝[Gcan1,Gcan2...Gcanl...GcanL]TRepresents; according to the target G and the ghost G22With respect to Building-1 symmetry, each candidate target G can be calculatedcanlOrdinate of the corresponding Building-1 wall:
then candidate target GcanlThe corresponding street widths are:
Dwl＝ywl-yc. (32)
preferably, the method comprises the following steps: the candidate target matching process in the step 5 is as follows:
5.1) obtaining each multipath time delay: and extracting echoes in the (mxn) th channel, and performing one-dimensional average-constant false alarm detection (CA-CFAR) on the echoes to obtain multipath time delay, wherein a time delay matrix is expressed as follows:
T＝[τ1,τ2...τq...τQ]T, (33)
where Q represents the number of multipaths in the echo.
5.2) candidate target GcanlMultipath delay calculation of (2): calculating electromagnetic waves along path PijFrom the m-th transmitting antenna to the candidate target GcanlAnd then returns to the time delay tau of the nth receiving antennal,ij：
In formulae (25) and (26), Gcanl,2And Gcanl,3Representing candidate objects GcanlIs reflected by the reflection path P2And P3Generating a false object which is symmetrical about Building-1 and Building-2, wherein the coordinates are as follows:
so candidate target GcanlWarp of warp PijMultipath time delay of propagation is taul,ij＝τi(Gcanl)+τj(Gcanl) (ii) a And after calculating the propagation delay of each path in the path matrix P, stacking the paths in the matrix:
Tl＝[τl,11,τl,12...τl,ij...τl,33]T. (37)
5.3) matching the candidate targets: to evaluate a candidate object GcanlSimilarity with the target G, delay matrix T based on the target G and candidate target GcanlDelay matrix T oflDefining a matching factor HlAnd error factor El：
Wherein the content of the first and second substances,
representing an absolute value operation, HlRepresenting a matrix T and a matrix TlNumber of successful matches of medium multipath, ElIndicating a corresponding match error;
and
the definition is as follows:
in the formula, TbIs a very small value empirical threshold;
5.4) target judgment rules: repeat 5.2 and 5.3 to calculate GcanThe two factors of all candidate targets in (1) are respectively stored in two matrixes:
H＝[H1,H2...Hl...HL]T, (41)
E＝[E1,E2...El...EL]T. (42)
according to factor HlAnd ElIf the candidate object G is to be foundcanlIf the judgment is the target, matching the factor HlAs the maximum value in the matrix H, error factor ElIs the minimum value in matrix E; based on this, the following rules are proposed:
if there is a unique maximum in the matrix H, the candidate target corresponding to the maximum is the target;
if the number of the maximum values in the matrix H is not 1, error factors corresponding to the subscripts of the maximum values of H need to be found out in E, the minimum values of the error factors are solved, and the candidate target corresponding to the minimum value is the target;
the first target determined by the rule is marked as Gt1The corresponding street width is marked as Dt1(ii) a Since the number of targets is unknown, G needs to be judgedcanWhether other targets exist; first, the target G is deleted from the matrices H and Et1Corresponding two factors, wherein the number of elements in H and E is L-1; then, the new target and street width are screened out by the rule and are marked as Gt2And Dt2If | Dt1-Dt2| is less than TD(TDError allowed by experiment), then Gt2When the judgment is made as the target, G needs to be continuously judgedcanWhether there are other objects, if | Dt1-Dt2| is greater than or equal to TDThen G ist2If not, the whole judgment process is ended; and if the scene is judged to have a plurality of targets, the street width is the average value of the street widths corresponding to the targets.
The advantages of this embodiment are: the target positioning can be still carried out when the scene layout information is incomplete; compared with the multipath separation series method, the invention avoids the tedious work of separating and distinguishing the multipath, and can effectively solve the multi-target problem at the same time; compared with the multipath accumulation series method, the method abandons the idea of image fusion, adopts the image combination method to process the imaged image, is less influenced by the environmental clutter and has high robustness.
Example 2
The invention will be further described with reference to the accompanying drawings and specific embodiments.
A system implemented with a non-line-of-sight target location method based on multiple-input multiple-output radar, comprising a memory having stored therein executable code, and a processor that, when executing the executable code, implements the method of any one of claims 1-9, in particular as follows:
performing two experiments of single target and double targets under a real L-shaped street, wherein in the two experiments, 2-transmission and 4-reception step frequency radars (M is 2, N is 4) are adopted as data acquisition equipment, and only the contribution of wall angle diffraction and wall surface first-order reflection to the target is considered; the general structure block diagram is shown in fig. 1, and comprises the following steps:
step 1: establishing a multipath signal model:
establishing a multipath propagation model: as shown in fig. 2;
step 2: generating a clear range image plane by preprocessing collected 1400-period radar echo data through windowing, zero padding, pulse compression, cable compensation, average cancellation and the like, wherein fig. 3 shows that the range image plane of a first channel is consistent with theoretical analysis, and a plurality of paths which are transmitted to a target through diffraction and reflection exist in radar echoes;
and step 3: taking the radar echo of the 744 th period in the range image plane as an example, performing back projection imaging and similar-back projection imaging, wherein the single-target imaging result is shown in fig. 4, and the (a) back projection imaging, (b) similar-back projection imaging, and (c) image correlation of fig. 4 are used for acquiring the target position;
the back projection imaged image shows several off-target blob regions, while the similar-back projection imaged image shows several rings of different radii centered at the corner C. The dual target imaging results are shown in fig. 5, and in fig. 5, (a) backprojection imaging, (b) similar-backprojection imaging, and (c) image correlation acquisition target positions. As the number of targets is increased, the number of multi-paths is increased, and the focusing area in the image is also increased;
and 4, step 4: respectively acquiring the centroid W and the central circle V of the focusing area in the two imaging results by using an image processing method, and then placing the centroid W and the central circle V in one imaging area for joint processing to obtain a candidate target, as shown by solid dots and hollow dots in a non-line-of-sight area in fig. 4 and 5 (c);
and 5: and (3) performing candidate target matching by taking the multipath length in the radar echo as a reference to obtain a target position and a street width, wherein the results of the two experiments are shown in the following table:
the above-mentioned embodiments are merely preferred embodiments for fully illustrating the present invention, and the scope of the present invention is not limited thereto. The equivalent substitution or change made by the technical personnel in the technical field on the basis of the invention is all within the protection scope of the invention. The protection scope of the invention is subject to the claims.
Claims (10)
1. The non-line-of-sight target positioning method based on the multi-input multi-output radar is characterized by comprising the following steps of: the method comprises the following steps:
acquiring partial layout information of a street, and constructing a multipath signal model and a multipath propagation model of a non-line-of-sight target;
preprocessing the collected multi-period radar echoes to generate a range profile;
selecting echo data of one period from a range image plane, and performing back projection imaging and similar-back projection imaging algorithm operation on the echo data to generate two images;
jointly processing the images generated by the two imaging steps by using an image processing method to obtain a candidate target;
extracting the time delay of each path from the distance image plane; and matching the candidate targets by taking the path delay as a reference, and screening out the real targets.
2. The method of claim 1, wherein: the multipath signal model is constructed in the following way:
constructing corner-shaped streets formed by multiple buildings, wherein the multiple buildings comprise Building-1 and Building-2;
acquiring the position [ x ] of a corner C close to one side of the radarc,yc]T；
Determining bitsTarget G ═ x in radar view blind zoneG,yG]T；
Let the m-th transmitting antenna and the n-th receiving antenna of the MIMO radar be Tm＝[xm,ym]T，Rn＝[xn,yn]T；
Street width DwDenotes the ordinate of Building-2 by ywRepresents;
the signal transmitted by the mth transmitting antenna is s (t), and the echo received by the nth receiving antenna is Zm,n(t)。
3. The method of claim 2, wherein: the echo received by the nth receiving antenna is represented by the following formula:
where s (t) represents a signal transmitted from the mth transmitting antenna, and I and J represent the number of paths through which an electromagnetic wave propagates from the transmitting antenna to a target (transmitting path) and returns from the target to a receiving antenna (receiving path), respectively; tau isi (m)(G) And τj (n)(G) The propagation time delay of the ith transmitting path and the jth receiving path; sigmai (m)And σj (n)Represents the backscattering coefficient; d (t) represents ambient noise and ξ (t) represents stationary clutter.
4. The method of claim 1, wherein: the multipath propagation model is constructed in the following way:
suppose that 3 one-way propagation paths P are abstracted from corner streetsiI ∈ {1,2,3}, where P1Represents a diffraction path; p2Representing a first order reflection path reflected on Building-1; p3Representing the first order of reflection on Building-2A reflected path; storing a round-trip path combination of the one-way path according to the following formula:
P＝[P11,P12...Pij,P33]T,i≤j,i,j∈{1,2,3}, (2)
where P denotes a path memory vector, PijA combination of round-trip paths representing a single-trip path;
electromagnetic wave follows path PijFrom transmitting antenna TmPropagates to the target G and returns to the receiving antenna RnThe time delay of (d) is calculated by the following formula:
τi,j (m,n)(G)＝τi (m)(G)+τj (n)(G) (3)
5. the method of claim 1, wherein: the back projection imaging is carried out according to the following steps:
dividing an imaging area into X multiplied by Y pixel points, wherein any pixel point is defined as p ═ X, Y]TExpressed, the pixel value calculation mode of the pixel point p is as follows:
in the formula, τBP (m)(p) shows electromagnetic waves from the transmitting antenna TmTime delay, tau, of straight line propagation to a pixel point pBP (n)(p) straight-line return to the receiving antenna R from the pixel point pnPropagation delay of (2); repeating the steps until the values of all pixel points in the imaging area are calculated, and using I to form an imageBPAnd (4) showing.
6. The method of claim 1, wherein: the similar-backprojection imaging is performed according to the following steps:
the pixel value calculation mode of the pixel point p is as follows:
wherein the round trip propagation delay tauBP-like (m,n)(p) is calculated by the following expression:
traversing and calculating pixel values of all pixel points in the imaging area to obtain an image IBP-like。
7. The method of claim 1, wherein: the two images generated by the joint imaging to generate the candidate target are specifically performed in the following manner:
extracting the centroid of the focusing ghost and the central circle of the focusing ring in the two images:
for image IBPPerforming two-dimensional average-constant false alarm detection operation to obtain sum image IBPThreshold matrix T of equal sizecaAnd then the image I is processed according to the threshold matrixBPBinaryzation;
communicating the focus areas in the binary image, calculating the mass center of the communicated areas, and stacking the coordinates in a matrix;
image I extraction by image processingBP-likeThe central circle of the middle focus circle, which is stacked in another matrix.
8. The method of claim 1, wherein: the candidate target is obtained by a centroid matrix and a central circle matrix, and the details are as follows:
two matrixes are distributed in the same imaging area according to positions and are based on an image IBPMiddle-to-first order reflection path P22Generated ghost G22And image IBP-likeMiddle diffraction path P11Generating a plurality of candidate targets G by jointly processing the centroid matrix and the central circle matrixcan＝[Gcan1,Gcan2,.......,GcanL]T；
According to the target G and the ghost G22Calculating each candidate target G according to the position characteristic of the symmetry of Building-1canlThe corresponding street width.
9. The method of claim 1, wherein: the candidate target matching process is performed according to the following steps:
acquiring each multipath time delay: extracting the echo in the mxn channel, carrying out one-dimensional average-constant false alarm detection on the echo to obtain multipath time delay, and stacking the multipath time delay in a time delay matrix T;
candidate target GcanlMultipath delay calculation of (2): calculating electromagnetic waves along path PijFrom the m-th transmitting antenna to the candidate target GcanlThen returning to the time delay of the nth receiving antenna by taul,ijRepresents; candidate target GcanlThe time delay of propagation along all paths in the path matrix P is:
Tl＝[τl,11,τl,12τl,ij...τl,33]T. (7)
matching the candidate targets: time delay matrix T based on target G and candidate target GcanlDelay matrix T oflDefinition of HlAnd ElTwo matching factors to represent the matrices T and T, respectivelylThe number of successful matching of the medium elements and the corresponding matching error;
target determination rules: repeat calculation GcanThe two factors of all candidate targets in (1) are respectively stored in two matrixes:
H＝[H1,H2...Hl...HL]T, (8)
E＝[E1,E2...El...EL]T. (9)
according to factor HlAnd ElScreening out a real target: if the candidate target G is to becanlIf the judgment is the target, matching the factor HlAs the maximum value in the matrix H, error factor ElIs the minimum value in the matrix E.
10. A multiple-input multiple-output radar based non-line-of-sight target locating system comprising a memory and a processor, wherein the memory has stored therein executable code which, when executed by the processor, implements the method of any one of claims 1-9.
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Citations (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005114601A (en) * | 2003-10-09 | 2005-04-28 | Alpine Electronics Inc | Navigation device and present position calculating method |
| US20120182173A1 (en) * | 2011-01-18 | 2012-07-19 | U.S. Government As Represented By The Secretary Of The Army | System and method for moving target detection |
| US20130100250A1 (en) * | 2011-10-07 | 2013-04-25 | Massachusetts Institute Of Technology | Methods and apparatus for imaging of occluded objects from scattered light |
| CN104062638A (en) * | 2014-06-18 | 2014-09-24 | 电子科技大学 | Multi-target detecting method used for through-wall radar |
| US20150022390A1 (en) * | 2013-07-22 | 2015-01-22 | Mitsubishi Electric Research Laboratories, Inc. | Method and System for Through-the-Wall Imaging using Sparse Inversion for Blind Multi-Path Elimination |
| CN104502911A (en) * | 2014-12-25 | 2015-04-08 | 湖南华诺星空电子技术有限公司 | Wall parameter estimation method of through-wall imaging radar |
| CN104914431A (en) * | 2015-05-05 | 2015-09-16 | 电子科技大学 | Focusing delay calculation method for known multilayer non-uniform walls |
| CN105549011A (en) * | 2015-12-16 | 2016-05-04 | 成都理工大学 | MIMO through-wall radar based single-side double-point squint imaging method of building |
| CN105974405A (en) * | 2016-05-04 | 2016-09-28 | 哈尔滨工业大学 | Amplitude weighting-based ground penetrating radar back projection imaging method |
| CN107589407A (en) * | 2017-08-29 | 2018-01-16 | 电子科技大学 | Front-back wall vibrates a multipaths restraint method after MIMO through-wall radar imaging |
| CN108919259A (en) * | 2018-08-29 | 2018-11-30 | 电子科技大学 | A kind of through-wall radar construction wall location acquiring method utilized based on multipath |
| CN109061622A (en) * | 2018-06-22 | 2018-12-21 | 电子科技大学 | A kind of concealed target multipath detection method based on millimetre-wave radar |
| CN109270526A (en) * | 2018-09-05 | 2019-01-25 | 电子科技大学 | A kind of corner object localization method for wall Location-Unknown |
| CN109298422A (en) * | 2018-11-14 | 2019-02-01 | 湖南华诺星空电子技术有限公司 | A kind of synthetic aperture imaging optimized treatment method, device for through-wall radar |
| CN109581317A (en) * | 2018-12-24 | 2019-04-05 | 电子科技大学 | One kind being based on the matched corner object localization method of echo-peak |
| CN111045006A (en) * | 2019-12-23 | 2020-04-21 | 电子科技大学 | Corner hidden target imaging method based on multi-imaging dictionary fusion |
| US20200158848A1 (en) * | 2018-11-16 | 2020-05-21 | Metawave Corporation | Method and apparatus for coded radar signals |
| US20200226783A1 (en) * | 2019-01-15 | 2020-07-16 | Arizona Board Of Regents On Behalf Of Arizona State University | Systems and methods for adaptive lighting for data-driven non-line-of-sight three-dimensional capabilities |
| CN112213724A (en) * | 2020-09-16 | 2021-01-12 | 深圳航天科技创新研究院 | Backward projection imaging method and system based on ground penetrating radar data and storage medium |
| US20210286087A1 (en) * | 2018-07-13 | 2021-09-16 | Nippon Telegraph And Telephone Corporation | Navigation satellite system reception device, method for processing navigation satellite signal from same, and program |
| CN113447915A (en) * | 2021-07-08 | 2021-09-28 | 电子科技大学 | Ultra-wideband tomography method suitable for complex multipath environment |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US11006383B2 (en) * | 2018-11-15 | 2021-05-11 | Arizona Board Of Regents On Behalf Of Arizona State University | Mapping and localization using image processing of wireless signals |
| JP2021135149A (en) * | 2020-02-26 | 2021-09-13 | Ｊｒｃモビリティ株式会社 | Dynamic target detection system, dynamic target detection method, and computer-executable program |
-
2021
- 2021-11-24 CN CN202111400940.6A patent/CN113960558B/en active Active
-
2022
- 2022-02-10 JP JP2022019755A patent/JP7142400B1/en active Active
Patent Citations (21)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2005114601A (en) * | 2003-10-09 | 2005-04-28 | Alpine Electronics Inc | Navigation device and present position calculating method |
| US20120182173A1 (en) * | 2011-01-18 | 2012-07-19 | U.S. Government As Represented By The Secretary Of The Army | System and method for moving target detection |
| US20130100250A1 (en) * | 2011-10-07 | 2013-04-25 | Massachusetts Institute Of Technology | Methods and apparatus for imaging of occluded objects from scattered light |
| US20150022390A1 (en) * | 2013-07-22 | 2015-01-22 | Mitsubishi Electric Research Laboratories, Inc. | Method and System for Through-the-Wall Imaging using Sparse Inversion for Blind Multi-Path Elimination |
| CN104062638A (en) * | 2014-06-18 | 2014-09-24 | 电子科技大学 | Multi-target detecting method used for through-wall radar |
| CN104502911A (en) * | 2014-12-25 | 2015-04-08 | 湖南华诺星空电子技术有限公司 | Wall parameter estimation method of through-wall imaging radar |
| CN104914431A (en) * | 2015-05-05 | 2015-09-16 | 电子科技大学 | Focusing delay calculation method for known multilayer non-uniform walls |
| CN105549011A (en) * | 2015-12-16 | 2016-05-04 | 成都理工大学 | MIMO through-wall radar based single-side double-point squint imaging method of building |
| CN105974405A (en) * | 2016-05-04 | 2016-09-28 | 哈尔滨工业大学 | Amplitude weighting-based ground penetrating radar back projection imaging method |
| CN107589407A (en) * | 2017-08-29 | 2018-01-16 | 电子科技大学 | Front-back wall vibrates a multipaths restraint method after MIMO through-wall radar imaging |
| CN109061622A (en) * | 2018-06-22 | 2018-12-21 | 电子科技大学 | A kind of concealed target multipath detection method based on millimetre-wave radar |
| US20210286087A1 (en) * | 2018-07-13 | 2021-09-16 | Nippon Telegraph And Telephone Corporation | Navigation satellite system reception device, method for processing navigation satellite signal from same, and program |
| CN108919259A (en) * | 2018-08-29 | 2018-11-30 | 电子科技大学 | A kind of through-wall radar construction wall location acquiring method utilized based on multipath |
| CN109270526A (en) * | 2018-09-05 | 2019-01-25 | 电子科技大学 | A kind of corner object localization method for wall Location-Unknown |
| CN109298422A (en) * | 2018-11-14 | 2019-02-01 | 湖南华诺星空电子技术有限公司 | A kind of synthetic aperture imaging optimized treatment method, device for through-wall radar |
| US20200158848A1 (en) * | 2018-11-16 | 2020-05-21 | Metawave Corporation | Method and apparatus for coded radar signals |
| CN109581317A (en) * | 2018-12-24 | 2019-04-05 | 电子科技大学 | One kind being based on the matched corner object localization method of echo-peak |
| US20200226783A1 (en) * | 2019-01-15 | 2020-07-16 | Arizona Board Of Regents On Behalf Of Arizona State University | Systems and methods for adaptive lighting for data-driven non-line-of-sight three-dimensional capabilities |
| CN111045006A (en) * | 2019-12-23 | 2020-04-21 | 电子科技大学 | Corner hidden target imaging method based on multi-imaging dictionary fusion |
| CN112213724A (en) * | 2020-09-16 | 2021-01-12 | 深圳航天科技创新研究院 | Backward projection imaging method and system based on ground penetrating radar data and storage medium |
| CN113447915A (en) * | 2021-07-08 | 2021-09-28 | 电子科技大学 | Ultra-wideband tomography method suitable for complex multipath environment |
Non-Patent Citations (6)
| Title |
|---|
| FAN, S., CUI, G., GUO, S., KONG, L., YANG, X.,YUAN, X: "Corner target positioning with unknown walls\' positions", 《THE JOURNAL OF ENGINEERING》, no. 19, pages 6143 - 6146, XP006085841, DOI: 10.1049/joe.2019.0176 * |
| S. LI ET AL.: "Multiple Targets Localization Behind L-Shaped Corner via UWB Radar", 《IEEE TRANSACTIONS ON VEHICULAR TECHNOLOGY》, vol. 70, no. 4, pages 3087 - 3100, XP011852507, DOI: 10.1109/TVT.2021.3068266 * |
| 樊士豪: "城市非直视盲区遮蔽目标定位方法研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》, no. 7, pages 136 - 767 * |
| 贾勇: "建筑物透视探测关键技术研究", 《中国博士学位论文全文数据库信息科学辑》, no. 3, pages 138 - 109 * |
| 郭世盛: "建筑环境多径信号抑制与利用方法研究", 《中国博士学位论文全文数据库 基础科学辑》, no. 1, pages 005 - 164 * |
| 郭飞: "基于UWB信号的高分辨时延估计与定位技术研究", 《中国优秀硕士学位论文全文数据库 信息科技辑》, no. 12, pages 136 - 345 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114578316A (en) * | 2022-04-29 | 2022-06-03 | 北京一径科技有限公司 | Method, device and equipment for determining ghost points in point cloud and storage medium |
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