A multi-target solution defuzzification and redundancy elimination method based on a multi-ary tree recursive model

Abstract

The application provides a multi-target ambiguity resolution and redundancy reduction method based on a multi-ary tree recursive model, comprising the following steps: step 1, according to a device repetition period parameter, a residual difference table is established for each two relatively prime repetition periods; step 2, after an apparent distance difference is obtained according to an apparent distance and a table is looked up to obtain an ambiguity, a target real distance is determined; step 3, according to the residual difference table, a matrix type staggered index two-dimensional table is established for a target index, a distance true value and a related repetition frequency index; and step 4, according to the established matrix type staggered index two-dimensional table, a method for obtaining multi-visibility of a target based on a multi-ary tree recursive model is adopted to perform a high-to-low fast search for multi-visibility of a target for all distance unit targets of each repetition period until the target is determined. The application effectively reduces redundancy of multi-target ambiguity resolution and improves processing speed.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of signal processing, in particular to a multi-target deblurring and deduplication method based on a multi-ary tree recursive model. BACKGROUND

[0002] When a radar adopts a high pulse repetition frequency (HPRF), and when the echo delay time of a target is greater than the repetition period of the transmitted pulse, range ambiguity will occur; when the radar adopts a low pulse repetition frequency (LPRF), and when the Doppler frequency caused by the target motion is greater than the repetition frequency of the transmitted pulse, velocity ambiguity will occur.

[0003] In order to solve the range ambiguity or the velocity ambiguity, the radar system generally has multiple pulse repetition period (PRT) working modes with multiple prime reciprocals, radio frequency frequency modulation working modes, etc. Among them, the multiple pulse repetition period (referred to as frequency difference) working mode is widely used in modern radars because of its high measurement accuracy and the advantages of being applicable to solving range ambiguity and velocity ambiguity at the same time.

[0004] The basic principle of deblurring by using the working mode with frequency difference is the remainder theorem. The remainder theorem, also known as the Sunzi theorem, is that when the divisors are prime reciprocals, if the remainders of the dividend divided by each divisor are known, the dividend can be uniquely determined (the dividend is less than the least common multiple of all the divisors). In engineering applications, the remainder table method based on the Sunzi theorem is used to solve range or velocity ambiguity.

[0005] The basic principle of the remainder table method of the Sunzi theorem is to use the difference (which can be negative) between the apparent distances (i.e. remainders) of the target on each repetition period to match the target to solve the ambiguity. However, any system inevitably has the problem of outliers, and any two apparent distances on any two PRTs (which are not necessarily the apparent distances of a target on different PRTs) can completely match a logical target distance point after two-dimensional remainder table matching, thereby causing the deblurring result to be incorrect. Of course, this situation can be discarded by merging. However, assuming that r1, r2, and r3 are the apparent distances of three different targets on three different PRTs, but can match into a target distance, the deblurring algorithm will still determine that there is a target at this distance unit (because the number of distance matches is 3), thereby causing a false judgment. This is the outlier problem of deblurring multiple targets by using the remainder table, i.e. the redundancy and error of multi-target deblurring.

[0006] The redundancy and error of multi-target range ambiguity are closely related to the number of targets and the size of the distance measurement error of the radar system. As the number of echoes on the same beam and the same velocity channel increases and the distance measurement error of the system increases, the false report probability generated by the deblurring algorithm will also increase. SUMMARY

[0007] The application provides a multi-target solution ambiguity de-redundancy method based on a multi-ary tree recursive model, which can be used to solve the technical problem of high false report probability caused by a solution ambiguity algorithm.

[0008] The application provides a multi-target solution ambiguity de-redundancy method based on a multi-ary tree recursive model, which comprises the following steps:

[0009] Step 1: According to the equipment repetition period parameter, a residual difference table is established for each two two-coprime repetition periods; wherein each table entry is (T i,j , N j,k ) under the count number k of the apparent distance difference T i,j , and T j,k is the apparent distance difference, and N i,j is the ambiguity.

[0010] Step 2: The apparent distance difference T j,k is obtained according to the apparent distance, and the ambiguity N i,j is obtained by table lookup, and then the target real distance is determined.

[0011] Step 3: According to the residual difference table, a matrix staggered index two-dimensional table is established.

[0012] Step 4: According to the established matrix staggered index two-dimensional table, the method for obtaining the multiple visibility of the target based on the multi-ary tree recursive model is adopted to perform a high-to-low fast search for the multiple visibility of the target for all distance unit targets of each repetition period until the target is determined.

[0013] Optionally, the residual difference table is in the following form:

[0014]

[0015] T i = r j -r i , i, j = 1, 2, 3 i≠j

[0016] Wherein: j represents the index of the reference PRT, r i is the apparent distance corresponding to the PRT j,k , N i,j is the ambiguity of the reference PRT, and the ambiguity of the smaller period in the two repetition periods is taken as the ambiguity in the residual difference table; the apparent distance difference is calculated once for each time interval that exceeds the time interval of any one period of the two repetition periods, and k is counted, and T i,j is the apparent distance difference.

[0017] Optionally, the apparent distance difference T j,k is obtained according to the apparent distance, and the ambiguity Nj,k Then, the target real distance is determined, comprising:

[0018] After the distance unit according to the constant false alarm threshold is condensed into a target, the corresponding apparent distance r of the target under the current repetition period is measured i , and the apparent distance difference T i,j under two different repetition periods is obtained.

[0019] According to the residual difference table, the corresponding ambiguity N j,k is found.

[0020] The true distance T is determined by the following method:

[0021] T = N j,k × PRT j + r j

[0022] In the formula, N j,k is the ambiguity, r j is the apparent distance corresponding to PRT j , and j represents the index of the reference PRT.

[0023] Optionally, the matrix staggered index two-dimensional table is established by the following method:

[0024] According to the matrix staggered index two-dimensional table Table[m, n]; m and n are used as subscripts and the subscript coding starts from zero; the subscript coding m represents different radar repetition periods, the subscript coding n represents different targets arranged in order from near to far according to the apparent distance, a two-dimensional table of different repetition periods and multiple targets is established, and the information in the table is filled; each element in the table includes the following information fields: repetition period index, target index, multiple visibility, and distance true value.

[0025] Wherein, the name, identification and explanation of each information field are shown in the following table:

[0026] Name Label Description Repetition Period Index index_prt Multi-repetition Period Encoding Target Index index_target Target Number Encoding, ordered by distance from near to far Multi-visibility visual_prt Record the number of times a target appears on different repetition periods Range Truth Value range Target Truth Value in units of range or time

[0027] Among them, the multiple visibility is used to count the multiple visibility of the target, and is cleared to zero in the initial state.

[0028] The matrix staggered index two-dimensional table is as follows:

[0029]

[0030] m represents the repetition period index, n represents the target index, and nNode represents the number of child nodes contained in a node of the multi-ary tree.

[0031] Optionally, according to the established matrix staggered index two-dimensional table, the method of multiple visibility of the target based on the multi-tree recursive model is used to search the multiple visibility of the target from high to low for all distance unit targets in each repetition period until the target is determined, including:

[0032] Starting from the index coding [m, 0] of the matrix staggered index two-dimensional table, the index is performed, the multi-tree is traversed from left to right, the index information of the first degree is processed first, index_prt=X, index_target=Y, and the target corresponding to the apparent distance is Z;

[0033] Starting from the [X, Y] element of the matrix staggered index two-dimensional table, the index information number is sequentially indexed from left to right until the terminal node at the bottom layer, all searches along a certain root path of the multi-tree are completed, and the search depth is given as the multiple visibility of the target;

[0034] The second degree of the [m, 0] element is indexed until the index information number in the table is 0;

[0035] When m takes the target value, the above steps are repeated until n traverses all values;

[0036] The threshold value of the multiple visibility of all targets in the target repetition period is determined, and the target exceeding the threshold value is determined as the target

[0037] The present application uses the multi-tree recursive model to count the multiple target visibility of the target through the matrix staggered index two-dimensional table, recursively indexes the established two-dimensional matrix staggered table according to different repetition periods and different distance units, counts the repetition period visibility of the distance unit with the target, and determines the target with the maximum repetition period visibility as the effective target in the case of multiple targets appearing in the same distance unit, thereby ensuring the probability of target correctness, effectively reducing the redundancy of multi-target ambiguity, and improving the processing speed. BRIEF DESCRIPTION OF DRAWINGS

[0038] Figure 1 The residual difference table method provided for the embodiment of the present application is shown in the figure;

[0039] Figure 2 The multi-tree established by the specific target residual difference table search provided for the embodiment of the present application is shown in the figure;

[0040] Figure 3 The multi-tree recursive search statistical repetition period visibility processing flowchart provided for the embodiment of the present application is shown in the figure. DETAILED DESCRIPTION

[0041] In order to make the purpose, technical scheme and advantages of the present application clearer, the embodiments of the present application will be described in further detail below with reference to the drawings.

[0042] The method provided in the application comprises:

[0043] Step 1, according to the device repetition period parameter, establishing a residual difference table for every two inter-prime repetition periods; wherein, each table entry in the residual difference table is (T i,j , N i,j ) under the count number k of the apparent distance difference T j,k , T i,j is the apparent distance difference, and N j,k is the ambiguity.

[0044] Specifically, the residual difference table is as follows:

[0045]

[0046]

[0047] T i,j = r i - r j , i, j = 1, 2, 3 i≠j

[0048] Wherein: j represents the index of the reference PRT, r i is the apparent distance corresponding to the PRT i , N j,k is the ambiguity of the reference PRT, and the ambiguity of the smaller period in the two repetition periods is taken as the ambiguity in the residual difference table; the time corresponding to the distance unit where the target is located exceeds the time interval of any one period in the two repetition periods, and the apparent distance difference is calculated once, and k is counted.

[0049] Step 2, according to the apparent distance, the apparent distance difference T i,j is obtained, the ambiguity N j,k is obtained by table lookup, and then the real distance of the target is determined.

[0050] Specifically, after the distance unit with a constant false alarm threshold is coagulated into a target, the apparent distance r i corresponding to the target under the current repetition period is measured, and the apparent distance difference T i,j under two different repetition periods is obtained.

[0051] According to the residual difference table, the corresponding ambiguity N j,k is found.

[0052] The true distance T is determined by the following method:

[0053] T = N j,k × PRT j + r j

[0054] wherein N j,k is the ambiguity, r j is the apparent distance of the corresponding PRT j and j represents the index of the reference PRT.

[0055] Step 3, according to the residual error table, a matrix interleaved index two-dimensional table is established.

[0056] Specifically, according to the matrix interleaved index two-dimensional table Table[m, n]; m and n are the starting index codes; the index code m represents different radar repetition periods, and the index code n represents different targets arranged in order from near to far according to the apparent distance, a two-dimensional table of different repetition periods and multiple targets is established, and the information in the table is filled; each element in the table contains the following information fields: repetition period index, target index, multiple visibility, and distance true value;

[0057] Wherein, the name, identification and explanation of each information field are shown in the following table:

[0058] Name Label Description Repetition Period Index index_prt Multi-repetition Period Encoding Target Index index_target Target Number Encoding, ordered by distance from near to far Multi-visibility visual_prt Record the number of times a target appears on different repetition periods Range Truth Value range Target Truth Value in units of range or time

[0059] Wherein, the multiple visibility is used to count the multiple visibility of the target, and is cleared in the initial state;

[0060] The matrix interleaved index two-dimensional table is as follows:

[0061]

[0062] m represents the repetition period index (i.e. the meaning of index_prt), n represents the target index (i.e. the meaning of index_target), and nNode represents the number of child nodes contained in a node of the multi-way tree.

[0063] Step 4, according to the established matrix interleaved index two-dimensional table, the method of calculating the multiple visibility of the target based on the multi-way tree recursive model is used to quickly search the multiple visibility of the target from high to low for all distance units of the target in each repetition period, until the target is determined.

[0064] Specifically, starting from the index code [m, 0] of the matrix interleaved index two-dimensional table, the index is performed, the multi-way tree is traversed from left to right, the index information of the first degree is processed first, index_prt=X, index_target=Y, and the target corresponding to the apparent distance is Z;

[0065] Starting from the [X, Y] element of the matrix interleaved index two-dimensional table, the index information is sequentially indexed from left to right, until the terminal node at the bottom layer is reached, all searches along a root path of the multi-way tree are completed, and the search depth is given as the multiple visibility of the target;

[0066] The second degree of the element [m, 0] is started to be indexed until the index information number in the table is 0, then the terminal node of the bottom layer is searched, and the target one-time multi-branch tree search is completed;

[0067] When m takes the target value, the above steps are repeated until n traverses all values;

[0068] Threshold threshold determination is performed on the multiple visibility of all targets in the target repeated period, and the target exceeding the threshold threshold is determined as the target. The target corresponding to the repeated period is eliminated in the matrix staggered index two-dimensional table.

[0069] The method provided by the application will be described below in combination with specific embodiments.

[0070] The specific embodiments of the application will be described in detail below in combination with the parameter settings of Table 1.

[0071] Table 1 is the detection distance and ambiguity of four targets under 173us, 257us, 310us and 800us pulse repetition interval (PRT) respectively based on the residual difference table lookup method simulation of the ambiguity principle of the Sunzi theorem. There is no distance ambiguity for the target under 800us repetition period, which can be used as the true value under the other three PRTs for verification of the target ambiguity resolution under the other three repetition periods. The apparent distance corresponding to the four targets under 800us is 186.8us, 213.4us, 295.4us and 386.4us respectively, and the apparent distance and ambiguity corresponding to the other three high repetition periods are shown in Table 1. For convenience, the distance information of the target is expressed in time units proportional to it, that is, the speed of electromagnetic wave is removed.

[0072] Table 1 Ambiguity and corresponding apparent distance of target under different repetition periods

[0073]

[0074] The basic principle of ambiguity resolution based on the residual difference table lookup method of the Sunzi theorem is to select one PRT, take the apparent distance of the target on the PRT as the reference, subtract the apparent distance on each PRT from the reference, and take the difference as the lookup item in the lookup table.

[0075] Taking a three-PRT system as an example, the repetition periods are PRT i , i = 1, 2, 3, representing three mutually prime pulse repetition periods, such as PRT1 = 173us, PRT2 = 257us, PRT3 = 310us in Table 1. When the target is at a distance unit T (true distance), as shown by the dashed line in Figure 1 , its remainder (i.e. apparent distance) on each PRT is

[0076] r i = T - N i × PRT i = T % PRT i , i = 1, 2, 3, (1)

[0077] where: r i is the apparent distance corresponding to PRT i , such as 13.8 (r1=13.8) corresponding to the 28Km target in Table 1 under the 173us repetition period;

[0078] N i is the ambiguity corresponding to PRT i , such as 1 (N1=1) corresponding to the 28Km target in Table 1 under the 173us repetition period;

[0079] % means the remainder.

[0080] Therefore, we have:

[0081] T = N1× PRT1 + r1 = N2× PRT2 + r2 = N3× PRT3 + r3 (2)

[0082] According to the remainder theorem, when N1, N2, N3 are the smallest two two- prime integers, they are uniquely corresponding to T. That is, when selecting appropriate PRT combinations to ensure that N1, N2, N3 can be two two-prime integers, if the measured target on each PRT remainder is measured, the true distance T of the target can be uniquely solved.

[0083] To use the residual difference table method to solve ambiguity, first, we need to establish the residual difference table (T i,j , N j ):

[0084] T i,j = r i - r j , i, j = 1, 2, 3 i≠j (3)

[0085] where: j represents the index of the reference PRT.

[0086] T i,j represents the difference between the apparent distance of a certain distance unit on each PRT i and the apparent distance on the reference PRT j ;

[0087] N j is the ambiguity of the distance unit on the reference PRT j .

[0088] If the first repetition period is taken as the reference period, then j = 1, and each table entry stored in the residual difference table is (Ti,1 T = N1), where T is the table value i,1 = r i - r1, i = 2, 3, j = 1. For a certain combination of the remainder difference value, the value of ambiguity N of the reference PRT is unique. Thus, there are two table values in each group of table entries, the first one represents the difference value of the target range unit in a certain range unit segment, and the second one is the ambiguity of the reference PRT. When a group of range units is obtained, i.e. the range in the first repetition period (PRT1) is taken as the reference, the differences between the ranges in other repetition periods and the reference are taken as the searching basis, and the searching is performed in the table stored in advance, so that the range unit segment value corresponding to the first PRT1 is N1, and finally the real range T = N1xPRT1 + r1 can be obtained. In the searching process, the criterion is that the absolute difference between the difference value calculated from the range and the table value is minimum.

[0089] When the obtained range unit has an error, i.e. when the obtained range is r i + ΔR i , ΔR i represents the error value in each PRT, and the difference value of the obtained range is T' i,1 = r i + ΔR i - r1- ΔR1, since the difference of ±1 error (in practical application, the error of ±1 range unit is generally considered) is maximum 2 (4 when ±2 error), thus the process of solving ambiguity by using the table value is to find the table value combination which satisfies the following condition: the difference between the table value and the value is less than 3 (less than 5 when ±2 error), and the absolute value of the difference is minimum.

[0090] |T' i,j -T i,j | < 3, i, j = 1, 2, 3, i≠j (3)

[0091] The result obtained according to the minimum sum of the absolute values of the differences is called the result obtained by the remainder searching table method, and the result obtained according to the minimum sum of the squares of the differences is called the result obtained by the improved remainder searching table method, i.e. the possible range is calculated from the result obtained by the searching table method, and the real range of the target is judged according to the minimum mean square error. According to the T i,j thus obtained, the corresponding reference PRT j can be searched from the remainder table, and the ambiguity N j thus obtained is used to solve the ambiguity, and the result after solving the ambiguity is obtained. When the ranging error is considered, the result after solving the ambiguity also has a ±1 / ±2 error, i.e. the result after solving the ambiguity is T = N j x PRT j + r j + ΔR j .

[0092] First step, according to the two two difference table of repeating period

[0093] Firstly, according to the introduction of the residual table method based on Sunzi theorem in the fuzzy principle, the three repeating periods are two two residual tables, as shown in table 2.

[0094] Table 2 two two repeating period residual table

[0095]

[0096] Table 2 contains three residual tables Sheet1, Sheet2 and Sheet3, corresponding to (173us, 257us), (173us, 310us) and (257us, 310us) repeating period residual table. i,j Corresponding to the apparent distance difference, N j Corresponding to the ambiguity of the reference PRT, generally use the small period as the reference repeating period in two repeating periods, the time corresponding to the distance unit of the target is more than the time interval of any one period in two repeating periods, calculate the apparent distance difference T i,j , count by k, such as Figure 1 The position corresponding to the dashed line in the figure. The maximum value of k does not exceed the working range of the device, so N j Sometimes also recorded as N j,k , indicating the ambiguity of the reference PRT under the corresponding k value, such as N 1,k and N 2,k in table 2.

[0097] Second step, according to the apparent distance to calculate the distance difference T i,j , and look up the ambiguity N j,k

[0098] According to the constant false alarm threshold distance unit, the distance is condensed into target, and the apparent distance r i of the target corresponding to the current repeating period is measured respectively. First, calculate the apparent residual value T i,j of two two repeating periods, add the error value ± ΔR to the result, search in the corresponding residual table, find the ambiguity value N j,k under the corresponding k value, and according to the formula T = N j,k × PRT j + r j , the true value distance T of the target is calculated, and the corresponding information is recorded, and the matrix type staggered index two-dimensional table is established, as shown in table 6.

[0099] Third step, two two matching is carried out by using residual table method, and matrix type staggered index two-dimensional table is established

[0100] The matrix staggered index two-dimensional table Table[m][n] is established according to Table 1. The subscript m (also referred to as the row number) of the two-dimensional table represents different radar repetition periods, for example, the PRTs for range deambiguating in Table 1 are three, 173us, 257us and 310us, and m=0, 1, 2 correspond to the three PRTs respectively; for the convenience of software programming, m and n are coded from zero as the subscripts.

[0101] The subscript n (also referred to as the column number) of the two-dimensional table represents different targets, for example, the four targets (28Km, 32Km, 44.3Km and 57.96Km) in Table 1, that is, n=0, 1, 2, 3 represent the four targets respectively. In actual processing, because of the range ambiguity, the real position of the target is uncertain, and therefore the index n is indexed according to the apparent distance from far to near, for example, in Table 1, when m=1, n=0 represents the 44.3Km target, n=1 represents the 57.96Km target, n=2 represents the 28Km target, and n=3 represents the 32Km target. Their apparent distances are 38.4us, 129.4us, 186.8us and 213.4us respectively, and they are arranged in order from near to far according to the apparent distance, to establish the two-dimensional table of different repetition periods and multiple targets, and then fill in the information in the table. Each element in the table contains the following information fields:

[0102] Table 3 Matrix Staggered Index Two-Dimensional Table Contains Fields

[0103] Name Label Description Repetition Period Index index_prt Multi-repetition Period Encoding Target Index index_target Target Number Encoding, ordered by distance from near to far Multi-visibility visual_prt Record the number of times a target appears on different repetition periods Range Truth Value range Target Truth Value in units of range or time

[0104] index_prt: represents the repetition period index, for example, the residual difference table established by two repetition periods of 173us and 257us, in Table 1, m=0 represents the coding of 173us, and the coding of 257us is embodied in the index_prt field, that is, index_prt=1 represents 257us; similarly, the residual difference table established by two repetition periods of 173us and 310us, index_prt=2 represents the coding of 310us.

[0105] index_target: represents the target index, the 28Km target, in the residual difference table established by two repetition periods of 173us and 257us, in Table 1, n=0 represents the target in 173us, and the 28Km target corresponding to 257us is represented by index_target. index_target=2 represents the 28Km target (the index number is indexed from small to large according to the apparent distance) corresponding to 257us repetition period. Similarly, the residual difference table established by two repetition periods of 173us and 310us, index_target=1 represents the coding of the 28Km target.

[0106] visual_prt: for the multiple visibility of the target, temporarily clear it.

[0107] range: represents the real distance of the detection, for the 28Km target, range = 186.8.

[0108] In Table 1, taking the 28Km target as an example, three kinds of repetition periods can be seen, so the element with the subscript m = 0, n = 0 in the two-dimensional interleaved matrix table contains the following information:

[0109] Table 4 173us repetition period and the rest two kinds of repetition period difference table index information

[0110] m=0 (173us), n=0 (28Km) 257us 310us index_prt 1 2 index_target 2 1 visual_prt 0 0 range 186.8 186.8

[0111] If there are other repetition periods that perform difference table deambiguating with 173us for 28Km target, the relevant index information is also established in the element with the subscript [0, 0], and the number of index information is also recorded. In Table 4, there are two index information (index information of 173us / 257us difference table, and index information of 173us / 310us difference table).

[0112] The difference index information of 257us and 310us for 28Km target is as follows

[0113] Table 5 257us and 310us repetition period difference table index information

[0114] m=1 (257us), n=0 (28Km) 310us index_prt 2 index_target 1 visual_prt 0 range 186.8

[0115] There is no need to perform difference table deambiguating information index between 257us and 173us, otherwise it will be repeated in Table 1, so only one index information of the difference table is recorded for the subscript [1, 0]. The deambiguating of 310us and 173us already exists in Table 4, so the number of all index information nodes for the subscript [2, n] is all zero. According to this method, the content in Table 1 is established into a two-dimensional matrix element table, as shown in Table 6.

[0116] Table 6 Matrix interleaved two-dimensional table

[0117]

[0118] In Table 6, m represents the repetition period index (i.e. the meaning of index_prt), n represents the target index (i.e. the meaning of index_target), and nNode represents the number of sub-nodes contained in a node of the multi-ary tree. The elements with dark background are the elements of the matrix interleaved two-dimensional index table formed by the de-masking of the 3 sheet residual tables for the target at a distance of 28 Km. Therefore, in Table 6, each element of the elements with m = 0 is a root node of a multi-ary tree, and the sub-nodes and terminal nodes thereof can be found according to the table index, as shown in Figure 2

[0119] In the fourth step, the multi-visibility of the target is found by using the multi-ary tree recursive model.

[0120] For the detection of different targets by the irregular PRF in Table 1, the matrix interleaved two-dimensional index table shown in Table 6 is established. Starting from the index table element with subscript [0, 0] of the target, the degree of the root node [0, 0] is 2 (nNode), and the multi-ary tree is traversed from left to right. First, the index information of the first degree is processed, index_prt = 1 (repetition period index), index_target = 2 (target index), and the apparent distance of the target after de-masking is 186.8 us. The index subscript [1, 2] can find the target with the apparent distance of 186.8 us (28 Km) after de-masking. Starting from the index table element [1, 2], the index information is sequentially processed from left to right until the terminal node at the bottom layer is reached, and the search depth is given as the multi-visibility of the target. The path is ended, and the second degree of the element [0, 0] is indexed. Its index_prt = 2 (repetition period index), index_target = 1 (target index), and the subscript [2, 1] is set. At this time, the number of index information in the table is 0, and it is considered that the terminal node at the bottom layer is searched, and the multi-ary tree search of the target is completed. Actually, the last row in Table 6 has little significance, and it is only used to identify that the terminal node of the multi-ary tree is searched.

[0121] There are two elements in the subscript [0, 0] in Table 1. The first one is searched along Sheet 1 (173 us, 257 us), and then the second index information along Sheet 2 (173 us, 310 us) is searched. The index_prt = 2 (repetition period index corresponding to the residual table index), and the index_target = 1 (target index). The index subscript [2, 1] can find the terminal node at the bottom layer in Table 6, which coincides with the terminal node of the first index. Thus, the search of the first 28 Km target is completed, and the repetition period visibility is 3. The specific processing flow is shown in Figure 3 .​

[0122] The recursive search of all targets detected in the first heavy repetition period is performed (i.e., the search for all n in Table 6 when m=0), the multi-visibility of all targets in the repetition period is searched, the threshold value of the multi-visibility of each target in the repetition period is determined, and the target is confirmed through the threshold value, and the target corresponding to the repetition period is eliminated in Table 6.

[0123] The search of the first heavy repetition period is completed, and the search of all targets in the second heavy repetition period is performed (i.e., the search for all n in Table 6 when m=1), and the target confirmed when m=0 is eliminated, the threshold value determination of the multi-visibility target and the target confirmation are completed, and the target confirmation in all repetition periods is completed through the above cycle, so that the problem of multi-target distance ambiguity redundancy is solved as much as possible.

[0124] From the above analysis, it can be seen that the matrix staggered index two-dimensional table can be used to complete the search of all targets from left to right at the same time, and the search of the same target from top to bottom is also realized, the multi-visibility of the staggered repetition frequency is counted, and the target is confirmed according to the maximum visibility of the same target, so as to improve the correctness of distance ambiguity resolution, reduce the false alarm probability, and realize target ambiguity resolution.

[0125] The redundancy of multi-target ambiguity resolution generally considers the frame processing method, that is, the correlation between the front and rear frames is considered in the ambiguity resolution process. The real target must exist continuously near the distance unit where it is located, and the moving speed determines the possible distance interval between the front and rear frames. When the same target exists in the N frames, it is considered as a real target point distance.

[0126] In addition to the correlation between the target in the front and rear frames, the speed information of the target can also be used to help improve the accuracy of ambiguity resolution. For example, whether different apparent distance values are consistent can be judged to determine whether they belong to the echo of the same target.

[0127] However, in the spatial random scanning mode, the correlation between the front and rear frames is meaningless. In the random scanning mode, the front and rear frames point to different spatial positions, and different targets corresponding to the same distance unit may appear, which do not have the correlation. Using distance-speed correlation information to solve the redundancy of multi-target ambiguity resolution has a large workload, and it is likely that ambiguity resolution will also be performed in the speed space. When the target is more, the calculation amount is large.

[0128] Through the matrix staggered index two-dimensional table, the multi-target visibility of the target is counted by using the multi-branch tree recursive model, the two-dimensional matrix staggered table is recursively indexed according to different repetition periods and different distance units, the distance unit with the target is counted for the repetition period visibility, for the case that multiple targets appear in the same distance unit, the target with the maximum repetition period visibility is determined as the effective target, so that the probability of target correctness is ensured, the redundancy of multi-target demodulation ambiguity is effectively reduced, and the processing speed is improved

[0129] The above-described embodiments of the application do not constitute a limitation of the protection scope of the application.

Claims

1. A multi-target defuzzification and redundancy removal method based on a multi-branch tree recursive model, used for processing radar pulses, characterized in that, The method includes: Step 1: Based on the equipment repetition cycle parameters, establish a residual difference table for each pair of coprime repetition cycles; the residual difference table stores the apparent distance difference. Counting times Each of the following table entries is , For apparent distance difference, For ambiguity; Step 2: Calculate the apparent distance difference based on the apparent distance. And look up the table to find the ambiguity. Then, determine the true distance to the target; Step 3: Based on the residual table, establish a matrix-style interleaved index two-dimensional table; Step 4: Based on the established matrix-style interleaved index two-dimensional table, the method of finding the multiple visibility of the target based on the multi-branch tree recursive model is adopted. The multiple visibility of the target is quickly searched from high to low for all distance unit targets in each repeating cycle until the target is determined. Calculate the apparent distance difference based on the apparent distance. And look up the table to find the ambiguity. Next, determine the true distance to the target, including: After condensing the range into a target based on the constant false alarm rate (CFAR) threshold range cells, the apparent range of the target in the current repetition cycle is measured. And calculate the apparent distance difference under two different repetition periods. ; Find the corresponding ambiguity based on the residual table. ; The true distance T is determined by the following method: ； In the formula, For ambiguity, For the corresponding The distance of sight Indicates the index of the baseline PRT.

2. The method according to claim 1, characterized in that, A matrix-style interleaved indexed two-dimensional table is constructed using the following method: Based on the establishment of a matrix-style interleaved index two-dimensional table Table[m, n], where m and n are subscript codes starting from zero, subscript code m represents different radar repetition periods, and subscript code n represents different targets arranged in order of apparent distance from near to far, a two-dimensional table of different repetition periods and multiple targets is established, and then the information in the table is filled in; each element in the table should contain the following information fields: repetition period index, target index, multiple visibility, and distance true value; Among them, multiple visibility is used to count the multiple visibility of the target, and is initially set to zero.

3. The method according to claim 1, characterized in that, Based on the established matrix-style interleaved index two-dimensional table, a method for calculating the multiple visibility of targets using a multi-branch tree recursive model is adopted. For each repeating cycle, the multiple visibility of targets in all distance units is rapidly searched from high to low until the target is determined, including: Starting from the index encoding [m,0] of the matrix-style interleaved index two-dimensional table, indexing is performed. The multi-way tree is traversed from left to right. The index information of the first degree is processed first, index_prt=X, index_target=Y, which corresponds to the target with an apparent distance of Z. Starting from the [X,Y] element of the matrix-interlaced indexed two-dimensional table, the index continues from left to right according to the number of indexed information until the lowest-level terminal node is reached. This completes all searches down from a certain root path of the multi-branch number and provides the search depth as the target's multi-visibility. Start indexing from the second degree of the element [m,0] until the number of indexes in the table is 0; When m takes the target value, repeat the above steps until n has traversed all values; A threshold is set for the multiple visibility of all targets under the target repetition cycle. If the visibility exceeds the threshold, it is identified as a target.

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