A two-dimensional spatial target pairing method based on distance-Doppler

Abstract

This invention discloses a two-dimensional spatial target pairing method based on range-Doppler, comprising the following steps: acquiring range-Doppler data generated by different paths when distributed radars transmit and receive radar signals, wherein the range-Doppler data includes: path features, range cells, amplitude, and Doppler values; wherein the path features include transmitting radar number R1 and receiving radar number R2; preprocessing the range-Doppler data to identify path types and generate a pairing data set; determining two-dimensional pairing conditions, wherein the two-dimensional pairing conditions include: range threshold and Doppler threshold; traversing the pairing data set and generating a pairing result dataset according to the two-dimensional pairing conditions. According to the above technical solution, based on the distance and Doppler relationship between targets and stations due to spatial location, a pairing algorithm can be used for filtering, improving the accuracy of successful pairing of real targets and reducing the false alarm rate.

Description

Technical Field

[0001] This invention relates to the field of radar communication technology, and more specifically, to a two-dimensional spatial target pairing method based on range-Doppler. Background Technology

[0002] With the continuous development of radar technology, various new radar systems are emerging, among which MIMO radar is quite representative. MIMO radar can be divided into centralized and distributed types. Distributed radar consists of a network of multiple radar sites located in different positions but working collaboratively. Through network connectivity and collaborative operation, it overcomes the limitations of a single radar operating from a single angle, achieving high-precision, all-around monitoring and tracking of targets. Generally, the signal waveforms transmitted by this type of radar need to have good orthogonality so that the radar can determine the signal source upon reception. In a multi-transmitter, multi-receiver configuration, the same target will generate echoes on different paths. Therefore, target spatial pairing is required for multiple paths to achieve fusion detection by the distributed radar. Target spatial pairing is a traditional yet highly challenging problem in distributed radar signal processing. When distributed radar performs centralized joint detection of targets, traditional signal processing methods such as orthogonal signals can separate each path. However, the information generated by the real target and the information generated by noise clutter are mixed together in each path, making it impossible to determine which is the real target information or which real target information corresponds to the same target. In existing technologies, pairing schemes mostly utilize only range information. However, for MIMO radar, especially distributed radar fusion detection technology, the key is to extract information about the same target on different radar paths, and then perform operations such as angle measurement, coordinate determination, and track tracking. This can be achieved by starting with the positional relationship between the distributed radar and the target, and exploring the relationship between the echo information generated by the same target on different paths in terms of range and Doppler frequency shift. Therefore, other information, such as Doppler information, exists in the echoes generated by the target on different paths, which is also of great significance for joint signal detection.

[0003] Therefore, a distance-Doppler two-dimensional spatial pairing method that combines distance and Doppler information is needed. Summary of the Invention

[0004] To achieve the above objectives, this application provides a two-dimensional spatial target pairing method based on range-Doppler, comprising the following steps:

[0005] When distributed radars transmit and receive radar signals from each other, range-Doppler data generated by different paths are acquired. The range-Doppler data includes: path features, range cells, amplitude, and Doppler values. The path features include the transmitting radar number R1 and the receiving radar number R2.

[0006] The range-Doppler data is preprocessed to identify path types and generate paired data sets. The path types include: self-path and other-path. Self-path refers to path data where the transmitting radar number and the receiving radar number are the same, and other-path refers to path data where the transmitting radar number and the receiving radar number are different.

[0007] Determine the two-dimensional pairing conditions, which include: distance threshold and Doppler threshold;

[0008] Traverse the paired dataset and generate a paired result dataset based on the two-dimensional paired conditions.

[0009] The method for determining the distance threshold is as follows:

[0010] and in, To transmit the radar self-path delay, To receive the radar's self-path delay, ε1 is the time delay of the path between the transmitting radar and the receiving radar, and ε1 is the range threshold.

[0011] The method for determining the Doppler threshold is as follows:

[0012] in, To transmit radar self-path Doppler values, To receive the radar's path-Doppler values, ε1 represents the path delay between the transmitting and receiving radars, and ε2 represents the Doppler threshold.

[0013] Further preprocessing includes:

[0014] Exclude data that does not correspond to the round trip from its path;

[0015] Store the range-Doppler data in a range matrix A, denoted as A = [x1 x2 ... x...]. j ] T And: x j = [T,R1,R2,D,A,F], where j is the path number and j < total path count, T is the path type, R1 is the transmitting radar number, R2 is the receiving radar number, D is the path range cell, A is the amplitude, and F is the Doppler value.

[0016] Furthermore, traversing the pairing data set and generating a pairing result dataset based on the two-dimensional pairing conditions includes:

[0017] Extracted from the path in the pairing data set;

[0018] A radar pair is obtained from the self-path, the radar pair including a first radar and a second radar;

[0019] Determine whether the other paths formed by the radar pair meet the two-dimensional pairing conditions. The other paths formed by the radar pair include: the self path of R1, the self path of R2, and the other paths of R1 and R2.

[0020] The determination of whether the radar pair's path conforms to the two-dimensional pairing condition includes:

[0021] Extract its path from the paired dataset;

[0022] Extract the radar path from the path, where the radar path refers to the path between the transmitting radar number and the receiving radar number corresponding to the first and second radars.

[0023] Determine the three-way path, and determine whether the three-way path meets the distance threshold. If it does, add the three-way path to the result dataset.

[0024] The three-way path refers to: the self-path of the first radar, the self-path of the second radar, and the radar-to-other path.

[0025] Specifically, the method for traversing the paired dataset and generating a paired result dataset based on two-dimensional paired conditions includes the following steps:

[0026] Define a path storage matrix Y, represented as Y = [y1 y2 ... y k ] T , where y k The radar path dataset is represented as y. k = [R1,R2,DATA1,DATA2,DATA]; where k is the radar pair number, and DATA1 is the path data matrix of radar R1, expressed as: DATA1 = [m1 m2...m a ] T , where m a Let m be the detection data of the a-th group from the R1 self-path. a = [j,D,A,F], where a is the detection data number of the radar R1 on its own path, which is less than or equal to the number of radar R1's own path detection data;

[0027] DATA2 is the path data matrix of radar R2, represented as: DATA2=[n1 n2...n b ] T , where n b Let n be the detection data of the b-th self-path of R2. b = [j,D,A,F], where b is the detection data number of the radar R2's self-path, which is less than or equal to the number of radar R2's self-path detection data;

[0028] DATA is the path data matrix for radars R1 and R2, represented as: DATA = [o1 o2...o c ] T , where o c The detection data for its path is represented as o. c = [j,D,A,F], where c is the detection data number of its path, which is less than or equal to the number of detection data of its path;

[0029] Data is extracted from the distance matrix A and stored in the path storage matrix Y;

[0030] Traverse the path to store the matrix Y and output the resulting dataset.

[0031] Furthermore, traversing the path storage matrix Y to output the result dataset includes the following steps:

[0032] Step S1: Initialize the parameters, define k=1, a=1, b=1, c=1, and execute step S2;

[0033] Step S2: Extract the radar pair array y from Y. k Proceed to step S3;

[0034] Step S3: Extract the radar pair array y k m a n b Proceed to step S4;

[0035] Step S4: Based on R1 and R2, from y k Extract its path o c Proceed to step S5;

[0036] Step S5: Determine m a n b o c Does it meet the distance threshold? If it does, then m a n b o c After adding the results dataset, proceed to step S6;

[0037] Step S6: Define c = c + 1, and determine o c Does it exist? If it exists, proceed to step S4; otherwise, proceed to step S7.

[0038] Step S7: Define b = b + 1, c = 1, and determine n. b Does it exist? If it exists, proceed to step S3; otherwise, proceed to step S9.

[0039] Step S9: Define a = a + 1, b = 1, c = 1, and determine m. aDoes it exist? If it exists, proceed to step S3; otherwise, proceed to step S10.

[0040] Step S10: Define k = k+1, a = 1, b = 1, c = 1, and determine y. k If it exists, proceed to step S2; otherwise, output the result dataset.

[0041] Specifically, when extracting data from distance matrix A and storing it into path storage matrix Y, the self-path data and other path data of R1 and R2 are judged, and if the pairing conditions are met, they are stored.

[0042] The judgment condition is expressed as: the distance of the round-trip path is consistent with the Doppler information, which is expressed as:

[0043]

[0044] Where ε1 is the distance threshold and ε2 is the Doppler threshold.

[0045] According to the present invention, based on the original distance information, the Doppler relationship of the target on different paths is combined, which has a more stringent judgment standard. The algorithm filters out fewer false targets, resulting in a higher matching accuracy. Attached Figure Description

[0046] Figure 1 This is a flowchart illustrating the steps of a two-dimensional spatial target pairing method provided in an embodiment of the present invention;

[0047] Figure 2 This is a flowchart illustrating the steps of a method for generating a pairing result dataset according to an embodiment of the present invention;

[0048] Figure 3 This is a comparison chart of the success rates of two-dimensional spatial target pairing and one-dimensional pairing simulation experiments provided by an embodiment of the present invention;

[0049] Figure 4 This is a comparison chart of false alarm rates in simulation experiments of two-dimensional spatial target pairing and one-dimensional pairing, provided by an embodiment of the present invention. Detailed Implementation

[0050] When multiple radars detect one or more targets, the separated multipath information contains real target information and false target information, which are mixed and cannot be separated. The solution proposed in this invention utilizes the spatial position information of the radar base station and the target, and uses its mapping on the two-dimensional information of range and Doppler to perform pairing and separation, extract the real target information, eliminate the false target information, and combine the corresponding information of the target on each path, so as to subsequently combine angle measurement to reconstruct the coordinate position.

[0051] The specific implementation of the present invention will now be described in detail with reference to the accompanying drawings.

[0052] Figure 1 The present invention provides the steps of a two-dimensional spatial target pairing method based on range-Doppler, including:

[0053] Step S100: Acquire range-Doppler data generated by different paths when distributed radars transmit and receive radar signals to each other. The range-Doppler data includes: path features, range cells, amplitude, and Doppler values; wherein, the path features include transmitting radar number R1 and receiving radar number R2.

[0054] During the acquisition process, distributed radars transmit and receive radar signals to detect targets, perform conventional signal processing such as MTD, and obtain the data received by each station.

[0055] Step S110: Preprocess the distance-Doppler data, identify path types, and generate paired datasets; wherein, path types include: self-path and other-path;

[0056] Self-path refers to path data where the transmitted radar number and the received radar number are the same, for example: Radar 1-Target-Radar 1;

[0057] The path refers to the path where the radar number is sent and the radar number is received, for example, radar 1-target-radar 2; the bidirectional transmission and reception path between two radars is called the round-trip path, for example, radar 1-target-radar 2 and radar 2-target-radar 1.

[0058] For the same target, the target echo distance and Doppler information obtained from the round-trip path (such as radar 1-target-radar 2 and radar 2-target-radar 1) should be the same. Therefore, in the preprocessing process in this step, after identifying the path type, it is determined whether there is corresponding data in the separated path that appears in both the round-trip path. The corresponding data is retained and arranged in pairs, and the data that cannot be found to correspond to the round-trip path is excluded, that is, the data that does not belong to the round-trip path is excluded.

[0059] Afterwards, path data that does not belong to the round trip will be cleared and stored.

[0060] Specifically, the range-Doppler data is stored in a range matrix A, represented as A = [x1 x2 ... x...]. j ] T And: x j The specific dataset for the path is denoted as x. j = [T,R1,R2,D,A,F], where j is the path number and j < total path count, T is the path type, R1 is the transmitting radar number, R2 is the receiving radar number, D is the path range cell, A is the amplitude, and F is the Doppler value.

[0061] Step S101: Determine the two-dimensional pairing conditions, which include: a distance threshold and a Doppler threshold;

[0062] Specifically, the method for determining the distance threshold is as follows:

[0063] and

[0064] in, To determine the time delay for transmitting the radar self-path (e.g., radar 1-n-radar 1 path), To receive the radar's self-path delay, The time delay of the path (radio 1 - radar 2) between the transmitting radar and the receiving radar is ε1, which is the distance threshold. When determining the distance threshold, the time delay is converted into the path distance unit: where the time delay is equal to twice the distance divided by the speed of light, and the path distance unit is a discrete distance.

[0065] The method for determining the Doppler threshold is as follows:

[0066]

[0067] in, To transmit radar self-path Doppler values, fa n b To receive the radar's path-Doppler values, fb n a ε1 represents the path delay between the transmitting and receiving radars, and ε2 represents the Doppler threshold.

[0068] Step S120: Traverse the pairing data set and generate a pairing result dataset based on the two-dimensional pairing conditions.

[0069] The process includes the following steps:

[0070] Extracted from the path in the paired dataset;

[0071] The radar pair is obtained from the self-path, which includes the first radar and the second radar, such as the self-path of R1 and the self-path of R2.

[0072] To determine whether the paths formed by the radar pairs meet the two-dimensional pairing conditions, the paths formed by the radar pairs include: the self-path of R1, the self-path of R2, and the paths formed by R1 and R2.

[0073] The specific process of determining whether the radar path constitutes a two-dimensional pairing condition includes the following steps:

[0074] 1) Extract its path from the paired dataset;

[0075] 2) Extract the radar path from the path, where the radar path refers to the path between the first radar and the second radar corresponding to the transmitting radar number and the receiving radar number.

[0076] 3) Determine the three-way path, which refers to: the self-path of the first radar, the self-path of the second radar, and the other path of the radar.

[0077] 4) Determine whether the data of the three-way path meets the distance threshold. If it does, add the data of the three-way path to the result dataset.

[0078] The implementation method for this step includes the following:

[0079] 1) Define the path storage matrix Y, represented as Y = [y1 y2 ... y k ] T , where y k The radar path dataset is represented as y. k = [R1,R2,DATA1,DATA2,DATA]; where k is the radar pair number, and DATA1 is the self-path data matrix of radar R1, expressed as: DATA1 = [m1 m2...m a ] T , where m a Let m be the detection data of the a-th group from the R1 self-path. a = [j,D,A,F], where a is the detection data number of the self-path of radar R1, which is less than or equal to the number of self-path detection data of radar R1; the self-path detection data contained in radar R1 is in the range of m. a In the middle, they are arranged in descending order of amplitude A;

[0080] For example, m1 = [10, 200, 0.8, 5] and m2 = [10, 260, 0.6, 8] represent two sets of detection data with path number 10 in the self-path of radar R1, respectively;

[0081] DATA2 is the self-path data matrix of radar R2, represented as: DATA2=[n1 n2...n b ] T , where n b Let n be the detection data of the b-th self-path of R2. b = [j,D,A,F], where b is the path number of the detection data of the radar R2's self-path, which is less than or equal to the number of self-path detection data of the radar R2; the self-path detection data of the radar R2 is in the range of n b In the middle, they are arranged in descending order of amplitude A;

[0082] DATA is the path data matrix for radars R1 and R2, represented as: DATA = [o1 o2...o c ] T , where o c The detection data for its path is represented as o. c = [j,D,A,F], where c is the detection data number of its path, less than or equal to the number of its paths, and the data of its path is in o c In the middle, they are arranged in descending order of amplitude A.

[0083] After definition, data is extracted from distance matrix A and stored in path storage matrix Y. During extraction, the self-path data and other-path data of R1 and R2 are evaluated. If a pairing condition is met, the data is stored. The evaluation condition is expressed as: the distance of the round-trip path is consistent with the Doppler information, expressed as:

[0084]

[0085] At this point, path information that does not meet this condition is considered false target information, and this step involves the elimination of some false target information.

[0086] 2) Determine whether the three paths meet the distance threshold. This process is as follows: Figure 2 As shown, it includes the following steps:

[0087] Step S200, input the storage matrix Y;

[0088] Step S210: Load the processing function. The processing function executes step S220, traverses the storage matrix Y, and performs the following operations:

[0089] Step S1: Initialize the parameters, define k=1, a=1, b=1, c=1, and execute step S2;

[0090] Step S2: Extract the radar pair array y from Y. k Proceed to step S3;

[0091] Step S3: Extract the radar pair array y k m a n b Proceed to step S4;

[0092] Step S4: Based on R1 and R2, from y k Extract its path o c Proceed to step S5;

[0093] Step S5: Determine m a n b o c Does it meet the distance threshold? If it does, then m a nb o c After adding the results dataset, proceed to step S6;

[0094] This invention also provides a more optimized processing solution, because m a n b o c The data in the results are all sorted from largest to smallest amplitude. Therefore, after determining the result set that meets the conditions, the data with the largest amplitude is obtained. At this point, step S6 is not required. c After evaluating the subsequent data, proceed directly to step S7 and enter the next round of traversal;

[0095] Step S6: Define c = c + 1, and determine o c Does it exist? If it exists, proceed to step S4; otherwise, proceed to step S7.

[0096] Step S7: Define b = b + 1, c = 1, and determine n. b Does it exist? If it exists, proceed to step S3; otherwise, proceed to step S9.

[0097] Step S9: Define a = a + 1, b = 1, c = 1, and determine m. a Does it exist? If it exists, proceed to step S3; otherwise, proceed to step S10.

[0098] Step S10: Define k = k+1, a = 1, b = 1, c = 1, and determine y. k If it exists, proceed to step S2; otherwise, output the result dataset.

[0099] This invention also provides a simulation experiment simulating the detection of two targets by four radar platforms: each of the four radars has its own path and other paths, generating a total of 16 paths. The simulation simulates the algorithm process of pairing the MTD data after radar signal transmission, reception, and processing with the input range-Doppler two-dimensional path information. Both range and velocity data are converted into detection range cells and Doppler channels for calculation. The simulation uses a Monte Carlo method and performs 200 repeated experiments. The number of successfully paired target points is recorded in each experiment, and a detection probability curve is plotted to verify the detection performance of this spatial registration system.

[0100] In each experiment, positive and negative random numbers are added to the path data of the real targets to simulate the error in the detection process, with the error magnitude increasing progressively. False targets are generated by random numbers from random paths, random distance cells, and random Doppler channels. After the real and false target data are constructed, the real target data is mixed with the false target data to form the input data for the spatial registration system. Simulations demonstrate that the false detection rate of the two-dimensional pairing algorithm is significantly lower than that of the one-dimensional algorithm. Figure 3 As shown, the false alarm changes are as follows Figure 4As shown.

[0101] The simulation experiments above verified the effectiveness and reliability of the proposed method, which can effectively reduce the possibility of false targets passing through the pairing. Based on the original pairing algorithm, it eliminates data with correct distance but Doppler error, thereby improving accuracy.

[0102] In summary, the range-Doppler two-dimensional spatial pairing method proposed in this invention solves the multipath fusion problem in distributed radar detection. Based on the distance and Doppler relationship between the target and the station due to their spatial location, the pairing algorithm is used for screening, which improves the accuracy of successful pairing of real targets and reduces false alarms. It has played a very good role in distributed radar fusion detection and provides assistance for subsequent angle measurement and positioning, track fusion and other work of distributed radar.

[0103] The above-disclosed embodiments are merely a few specific examples of the present invention. However, the present invention is not limited thereto, and any variations that can be conceived by those skilled in the art should fall within the protection scope of the present invention.

Claims

1. A two-dimensional spatial target pairing method based on range-Doppler, characterized in that, Includes the following steps: When distributed radars transmit and receive radar signals from each other, range-Doppler data generated by different paths are acquired. The range-Doppler data includes: path features, range cells, amplitude, and Doppler values. The path features include the transmitting radar number R1 and the receiving radar number R2. The range-Doppler data is preprocessed to identify path types and generate paired data sets. The path types include: self-path and other-path. The self-path refers to path data where the transmitting radar number and the receiving radar number are the same, and the other-path refers to path data where the transmitting radar number and the receiving radar number are different. Determine two-dimensional pairing conditions, which include: a distance threshold and a Doppler threshold; Traverse the pairing data set and generate a pairing result dataset based on the two-dimensional pairing conditions; The method for determining the distance threshold is as follows: and ,in, To transmit the radar self-path delay, To receive the radar's self-path delay, , The time delay of the path between the transmitting and receiving radars. This is the distance threshold. The method for determining the Doppler threshold is as follows: , ,in, To transmit radar self-path Doppler values, To receive the radar's path-Doppler values, , The time delay of the path between the transmitting and receiving radars. This is the Doppler threshold.

2. The two-dimensional spatial target pairing method according to claim 1, characterized in that, The preprocessing includes: Exclude data that does not correspond to the round trip from the other paths; The range-Doppler data is stored in a distance matrix A, represented as follows: ,and: , where j is the path number and j < total path, T is the path type, R1 is the transmitting radar number, R2 is the receiving radar number, D is the path range cell, A is the amplitude, and F is the Doppler value.

3. The two-dimensional spatial target pairing method according to claim 2, characterized in that, The step of traversing the pairing data set and generating a pairing result dataset based on the two-dimensional pairing conditions includes: Extracted from the path in the pairing data set; A radar pair is obtained from the self-path, the radar pair including a first radar and a second radar; Determine whether the other paths formed by the radar pair meet the two-dimensional pairing conditions. The other paths formed by the radar pair include: the self path of R1, the self path of R2, and the other paths of R1 and R2.

4. The two-dimensional spatial target pairing method according to claim 3, characterized in that, The determination of whether the radar pair's path conforms to the two-dimensional pairing condition includes: Extract its path from the paired data set; Extract the radar path from the other path, where the radar path refers to the other path of the first radar and the second radar corresponding to the transmitting radar number and the receiving radar number. Determine the three-way path, and determine whether the three-way path meets the distance threshold. If it does, add the three-way path to the result dataset. The three-way path refers to: the self-path of the first radar, the self-path of the second radar, and the radar-to-other path.

5. The two-dimensional spatial target pairing method according to claim 4, characterized in that, The method for traversing the pairing data set and generating a pairing result dataset based on the two-dimensional pairing conditions includes the following steps: Define the path storage matrix Y, denoted as ,in, For radar path datasets, represented as Where k is the radar pair number, The path data matrix of radar R1 is represented as follows: ,in, Let the detection data of group a from path R1 be represented as 'a' is the detection data number of the radar R1 on its own path, which is less than or equal to the number of radar R1's own path detection data. The path data matrix of radar R2 is represented as follows: ,in, Let the detection data of the b-th self-path of R2 be represented as: b is the detection data number of the radar R2's self-path, which is less than or equal to the number of radar R2's self-path detection data. The other path data matrix for radars R1 and R2 is represented as follows: ,in, The detection data for its path is represented as c is the detection data number of its path, which is less than or equal to the number of detection data of its path; Data is extracted from the distance matrix A and stored in the path storage matrix Y; Traverse the path to store the matrix Y and output the resulting dataset.

6. The two-dimensional spatial target pairing method according to claim 5, characterized in that, The process of traversing the path storage matrix Y to output the dataset includes the following steps: Step S1: Initialize parameters, define k=1, a=1, b=1, c=1, and execute step S2; Step S2: Extract radar pair array from Y Proceed to step S3; Step S3: Extract the radar pair array In , Proceed to step S4; Step S4: Based on R1 and R2 from Extract its path Proceed to step S5; Step S5: Determine , , Does it meet the distance threshold? If it does, then... , , After adding the results dataset, proceed to step S6; Step S6: Define c = c + 1, and determine... Does it exist? If it exists, proceed to step S4; otherwise, proceed to step S7. Step S7: Define b = b + 1, c = 1, and determine... Does it exist? If it exists, proceed to step S3; otherwise, proceed to step S9. Step S9: Define a = a + 1, b = 1, c = 1, and determine... Does it exist? If it exists, proceed to step S3; otherwise, proceed to step S10. Step S10: Define k=k+1, a=1, b=1, c=1, and determine... If it exists, proceed to step S2; otherwise, output the result dataset.

7. The two-dimensional spatial target pairing method according to claim 5, characterized in that, When extracting data from the distance matrix A and storing it into the path storage matrix Y, the self-path data and other path data of R1 and R2 are judged, and if the pairing conditions are met, they are stored. The judgment condition is expressed as: the distance of the round-trip path is consistent with the Doppler information, which is expressed as: ， ； in, This is the distance threshold. This is the Doppler threshold.

Images