CN115236605A - PD radar pulse repetition frequency group selection method based on genetic algorithm - Google Patents
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Abstract
The invention discloses a PD radar pulse repetition frequency group selection method based on a genetic algorithm, which mainly solves the problems that the probability of matching false targets is high when a target is detected and the operation amount is large due to the fact that all repeated frequency combinations are processed in the prior art. The method comprises the following implementation steps: generating a PRT generating matrix meeting constraint conditions; calculating the fitness value of each big pulse group after repeated frequency dithering; adaptively updating a large pulse group in a PRT generating matrix through a genetic algorithm; judging whether the largest large pulse group in the fitness values in the PRT generating matrix which is continuously updated repeatedly is the same or not; and outputting the large pulse group corresponding to the maximum fitness value in the PRT generating matrix. The invention can quickly search the optimal pulse repetition frequency group to obtain the PD radar clear image which best meets the requirement, reduces the time cost, improves the accuracy of target information detection and improves the engineering application value of the invention.
Description
Technical Field
The invention belongs to the technical field of radars, and further relates to a Pulse Doppler (PD) radar Pulse repetition frequency group selection method based on a genetic algorithm in the technical field of radar signal processing. The method can be used for maximizing the radar clearness map area by optimizing the pulse repetition frequency group under the working mode that the PD radar is in the repetition frequency.
Background
When the PD radar works in a strong clutter background, clutter information is also present in echo data of the PD radar in addition to a target, and the clutter information needs to be suppressed. Because the Pulse Repetition Frequency (PRF) of the PD radar is higher and the number of Doppler filters is larger, the PD radar has a good inhibition effect on signals with low Frequency, and the clutter improvement performance may be better than Moving Target Detection (MTD). For PD radar, the detectable area on the range-doppler two-dimensional map is called a sharp map. And the distance, speed blind area and distance ambiguity problem caused by the high PRF of the PD radar can make the area of the clear image not meet the detection requirement. The problem is generally solved by adopting an N/M criterion (selecting N kinds of repetition frequencies from M kinds of repetition frequencies), and the distance ambiguity resolution and the blind compensation are jointly processed. The pulse repetition frequency group setting of the method is random, so that the obtained clear image area is probably not the largest, and certain performance loss exists.
The Western-Ann electronic science and technology university provides a method for searching an optimal pulse repetition frequency group of a radar in a patent document 'genetic algorithm-based airborne radar pulse repetition frequency group optimization method' (patent application No. 201410064471.9, application publication No. CN 10885033A), and then a radar distance-Doppler two-dimensional graph is obtained through calculation of the pulse repetition frequency group. The method comprises the steps of firstly defining constraint conditions of each pulse repetition time in a radar pulse repetition time group, then utilizing the radar pulse repetition time group to carry out blind complementing and distance ambiguity resolving operation so as to obtain a corresponding cost function to construct an optimization model, adopting a genetic algorithm to solve the optimization model, and finally obtaining an optimal pulse repetition frequency group. Although the algorithm can enable the radar to have good detection performance on a range-Doppler two-dimensional graph, the method still has two defects that blind area compensation and range ambiguity resolution are jointly processed by the method, and the probability of matching false targets is increased. Secondly, when the distance ambiguity is resolved, all the repetition frequency combinations need to be resolved, the operation time is long, and the requirement on hardware is high.
Disclosure of Invention
The invention aims to provide a PD radar pulse repetition frequency group selection method based on a genetic algorithm aiming at the defects of the prior art, and the method is used for solving the problems that the probability of matching a false target is increased and the operation time is too long when blind complementing and range ambiguity resolving are carried out on combined processing in the prior art.
The idea of the present invention to achieve the above object is that the present invention designs a pulse repetition frequency group through a genetic algorithm, and uses a repetition frequency dithering algorithm to solve the problems of easy matching to a false target and too long operation time. The reason is that, because the double-frequency dithering is used for distance-resolving blurring and blind-complementing processing, the double-frequency dithering is firstly carried out by adopting two pulse groups (namely the double frequencies of the two pulse groups are very close), and the double-frequency combination of the dithering is only used for distance-resolving blurring and removing far-zone targets. After a far-zone target is removed, another group of 'jittering' repetition frequency combination is adopted to carry out blind complementing operation on the previous repetition frequency combination, so that a PD radar distance-Doppler two-dimensional graph is formed, when a genetic algorithm is used for selecting a pulse repetition frequency group, the advantages of repetition frequency jitter are utilized, the calculation of the fitness is more comprehensive and accurate, and the problems of increasing the probability of matching a false target and large calculation amount are solved.
In order to achieve the purpose, the technical scheme adopted by the invention comprises the following steps:
generating a PRT generating matrix of Q rows and W columns, wherein each row in the matrix represents a PRT group of a big pulse group, and elements of each row represent the PRT of each small pulse group in the big pulse group; each element in the PRT generator matrix is in the range [ T 1 ,T 2 ]In the interior, satisfy p i(j+1) -p ij = Δ condition; wherein Q is more than or equal to 100, the value of W is determined by the area requirement of the PD radar clear image, and T is 1 And T 2 The value of (A) is determined by the detection range of the PD radar, and the unit is mus, p i(j+1) Representing the value of the element, p, in the ith row and j +1 column of the PRT generator matrix ij Representing the ith row in the PRT generator matrixElement values of j-th column, when j is odd, Δ =1 μ s;
step 2, calculating the fitness value of each big pulse group after repeated frequency dithering:
step 2.1, determining the fitness value of each grid unit in the distance-Doppler two-dimensional graph of each small pulse group;
2.2, sequentially carrying out distance-resolving fuzzy processing and blind-filling processing on each big pulse group by using a repetition frequency dithering method to obtain a distance-Doppler two-dimensional graph of the big pulse group after repetition frequency dithering processing, and calculating the adaptability value of each big pulse group according to the adaptability value of each grid unit in the distance-Doppler two-dimensional graph of each small pulse group;
step 3, adaptively updating the large pulse group in the PRT generating matrix through a genetic algorithm:
step 3.1, updating a PRT generating matrix by using a roulette algorithm;
step 3.2, performing cross operation on the big pulse group in the updated PRT generating matrix;
step 3.3, carrying out mutation operation on the large pulse group in the intersected PRT generating matrix;
step 4, judging whether the largest large pulse group in the fitness values in the PRT generating matrix which is updated by iteration for S times continuously is the same or not, wherein S is more than or equal to 5, if yes, executing the step 5; otherwise, executing step 2;
and 5, outputting the large pulse group corresponding to the maximum fitness value in the PRT generating matrix.
Compared with the prior art, the invention has the following advantages:
firstly, because the invention uses the repetition frequency dithering algorithm, the repetition frequencies of two dithered pulse groups are very close, so that only the specific repetition frequency combination is required to be subjected to distance ambiguity resolution, the defect that the probability of matching to a false target is increased in the prior art is overcome, the invention can correctly detect the target distance, and the accuracy of detecting the target information is improved.
Secondly, because the invention carries out step-by-step processing on the distance ambiguity resolution and blind-filling processing, calculates the fitness by utilizing the distance-Doppler two-dimensional graph of the PD radar and then selects the optimal pulse repetition frequency group by the genetic algorithm, the problem of large computation caused by processing all repetition frequency combinations in the prior art is solved, so that the invention can rapidly search the optimal pulse repetition frequency group to obtain the PD radar clear graph which best meets the requirement, thereby improving the operation efficiency of searching the optimal pulse repetition frequency group, reducing the time cost and improving the engineering application value of the invention.
Drawings
FIG. 1 is a flow chart of the method of the present invention;
FIG. 2 is a range-Doppler two-dimensional graph of a PD radar constructed using a prior art method;
FIG. 3 is a two-dimensional range-Doppler plot of a PD radar constructed using the method of the present invention.
Detailed Description
The invention is described in further detail below with reference to the figures and examples.
The implementation steps of the present invention are further described in detail with reference to fig. 1 and an embodiment.
Step 1.1, generating a pulse repetition period PRT (pulseRepetitiontiTime) generating matrix of W rows and Q columns, wherein each element in the PRT generating matrix is in a range [ T [ [ T ] 1 ,T 2 ]In, satisfy p i(j+1) -p ij = Δ condition; wherein, Q is more than or equal to 100, the value of W is determined by the area requirement of the PD radar clearness chart, T 1 And T 2 The value of (A) is determined by the detection range of the PD radar, and the unit is mus, p ij Represents the element value of the ith row and jth column in the PRT generation matrix, and Δ =1 μ s when j is an odd number.
In step 1.2, since a large pulse group consisting of a plurality of pulse groups of different PRTs needs to be used when the repetition frequency dithering is performed, the elements of the PRT generation matrix are associated therewith. Each row in the matrix represents a PRT corresponding to a group of large pulses, and each element in each row represents a PRT of a group of pulses.
In the examples of the present invention, Q =100,w =8,t is taken 1 ＝150μs，T 2 ＝360μs。
Step 2, calculating the fitness value of each big pulse group after repeated frequency dithering:
step 2.1, determining the fitness value of each grid unit in the distance-Doppler two-dimensional graph of each small pulse group;
step one, performing clutter suppression on each small pulse group in a Doppler dimension to obtain a Doppler detectable region of the small pulse group; after carrying out blind area detection on each small pulse group in a distance dimension, obtaining a distance detectable area of the small pulse group, and forming a distance-Doppler two-dimensional detection map of the small pulse group by the Doppler detectable area and the distance detectable area of each small pulse group;
secondly, traversing all grid cells in the distance-Doppler two-dimensional graph of each small pulse group, setting the fitness values of all grid cells of which the distance cells and the Doppler cells are in the detectable area to be 1, and setting the fitness values of the rest grid cells to be 0;
step 2.2, after the repetition frequency dithering is carried out on each big pulse group, a distance-Doppler two-dimensional graph after the repetition frequency dithering is obtained, and the adaptability value of each big pulse group is calculated according to the adaptability value of each grid unit in the distance-Doppler two-dimensional graph of each small pulse group;
step one, traversing each large pulse group, and performing de-blurring treatment on every two adjacent small pulse groups in the large pulse group, wherein the de-blurring treatment refers to AND operation on fitness values of the same grid unit in a distance-Doppler two-dimensional image of the two adjacent small pulse groups;
and secondly, performing blind complementing operation on the aorta group subjected to the distance ambiguity resolution, wherein the blind complementing operation refers to performing OR operation on the fitness values of the same grid unit in the distance-Doppler two-dimensional graph subjected to the distance ambiguity resolution.
Thirdly, calculating the adaptability value of each big pulse group by using the adaptability value of the grid unit of the distance-Doppler two-dimensional graph after each big pulse group is blinded, wherein the adaptability C corresponding to the ith big pulse group i Can be expressed as:
wherein, C i Representing fitness values corresponding to the ith large pulse group, h is more than or equal to 1 and less than or equal to W, h is an odd number, a =0,1,2, a, N, b =0,1,2, a, M, W represents the total number of columns in a PRT generating matrix, N represents the total number of distance units of the distance-Doppler two-dimensional map of the ith large pulse group, M represents the total number of Doppler units of the distance-Doppler two-dimensional map of the ith large pulse group, c represents the total number of Doppler units of the distance-Doppler two-dimensional map of the ith large pulse group ih (a, b) denotes the fitness value of a grid cell composed of the a-th range cell and the b-th Doppler cell in the h-th small pulse group of the i-th large pulse group, c i(h+1) (a, b) denotes the fitness value of the mesh unit composed of the a-th range unit and the b-th doppler unit in the h + 1-th small pulse group of the ith large pulse group.
Step 3, adaptively updating the big pulse group in the PRT generating matrix through a genetic algorithm:
step 3.1, updating a PRT generating matrix by using a roulette algorithm;
first, the selection probability of each group of large pulses in the PRT generator matrix is calculated using the following formula:
wherein, F i Representing the selection probability of the ith big pulse group in the PRT generating matrix, and Q representing the total number of rows in the PRT generating matrix;
and secondly, sequentially selecting V large pulse groups in the PRT generating matrix according to the selection probability by using a roulette algorithm, and sequentially replacing the large pulse groups with low fitness from high fitness in the V PRT generating matrices according to the selection sequence to obtain an updated PRT generating matrix.
Step 3.2, performing cross operation on the big pulse group in the updated PRT generating matrix;
the method comprises the steps that firstly, two large pulse groups k and l are randomly selected from an updated PRT generation matrix, and the two selected large pulse groups k and l are expressed into binary forms k 'and l';
second, random in k 'and l' expressed in binary formSelecting one bit as the intersection point of k 'and l', and taking the intersection probability of all bits after the intersection point of k 'and l' as r c Performing crossover operation to obtain the large pulse groups k 'and l', r after crossover operation c Is in the range of [0.5,1]A value randomly selected in the range;
cross probability r in the embodiments of the present invention c ＝0.6。
Thirdly, judging whether the pulse repetition period of each small pulse group in the large pulse groups k 'and l' is in [ T ] 1 ,T 2 ]If yes, representing k 'and l' as decimal, replacing k and l in the PRT generating matrix, and executing the fourth step; otherwise, executing the first step;
step four, judging whether the cycle number of the step is equal to Q, if so, executing the step 3.3, otherwise, executing the first step of the step;
step 3.3, carrying out mutation operation on the large pulse group in the intersected PRT generating matrix;
step one, randomly selecting a large pulse group t from a PRT generating matrix after crossing, and representing the selected large pulse group t into a binary form t';
second, randomly selecting a bit from t 'expressed in binary form as the variation point of t', and taking the bit of the variation point to inverse, with variation probability r m Performing mutation to obtain a mutated aortic group t', r m Is in the range of [0,0.5 ]]A value randomly selected in the range;
mutation probability r in the embodiments of the present invention m ＝0.2。
Thirdly, judging whether the pulse repetition periods of all the small pulse groups in the big pulse group T' are all in [ T ] 1 ,T 2 ]If yes, representing t' as decimal, replacing t in PRT generating matrix, and executing the fourth step; otherwise, executing the first step;
step four, judging whether the current cycle number is equal to Q, if so, executing step 4; otherwise, executing the first step of the step;
step 4, judging whether the largest large pulse group in the fitness values in the PRT generating matrix which is updated by iteration for S times continuously is the same or not, wherein S is more than or equal to 5, if yes, executing the step 5; otherwise, executing step 2;
when the largest large pulse group in the fitness value in the PRT generating matrix is the same after more than 5 times of iteration updating, the optimal pulse repetition frequency group can be found.
S =5 in the present embodiment.
And 5, outputting the large pulse group corresponding to the maximum fitness value in the PRT generating matrix.
The effect of the invention is further explained by combining simulation experiments as follows:
1. simulation experiment conditions
The hardware platform of the simulation experiment of the invention is as follows: the processor is Inteli7-6700CPU, the main frequency is 3.4GHz, and the memory is 8GB
The software platform of the simulation experiment of the invention is as follows: windows7 operating system and MATLAB R2016a.
The simulation parameters of the radar signals used in the simulation experiment of the invention are as follows: carrier frequency of f s =3GHz, 100m each range bin, 20Hz each doppler bin, 3000 range bins and 16 doppler channels for radar detection. The transmission pulse width is 14 mus, the PRT search upper limit is 360 mus, the pulse repetition frequency search lower limit is 150 mus, and the radar transmits 8 pulse repetition frequencies. Crossover probability r in genetic algorithm c =0.6, probability of variation r m =0.2, number of individuals in the starting population Q =100.
2. Simulation content and result analysis
The digital simulation experiment of the present invention includes two simulation experiments.
In the simulation experiment 1, after distance ambiguity resolution and blind area compensation are performed by adopting the prior art under the condition of the simulation experiment, a PD radar distance-doppler two-dimensional graph is obtained, and the result is shown in fig. 2. In fig. 2, black represents a blind area, gray represents a detectable area, the abscissa is a velocity dimension, and the ordinate is a distance dimension. It can be seen from fig. 2 that after the PD radar range-doppler two-dimensional map is constructed by using the prior art, besides the first blind area and the second blind area, many blind areas occur, which may affect the detection of the radar. The first blind area refers to a Doppler blind area for suppressing ground stationary clutter with Doppler frequency near 0, and the second blind area refers to a distance blind area formed by turning off a receiver when the radar transmits pulses. The PRT groups at this time are {209us,210us }, {221us,222us }, {270us,271us }, {320us,321us }.
The prior art refers to a method for constructing a range-doppler two-dimensional detection map by adopting an N/M (N/M) criterion, which is disclosed in a patent document 'genetic algorithm-based airborne radar pulse repetition frequency group optimization method' (patent application No. 201410064471.9, application publication No. CN 10885033A) applied by the university of electronic technology in Western Ann.
In the simulation experiment 2, under the condition of the simulation experiment, the optimal PRT group is searched by adopting the PD radar pulse repetition frequency group selection method based on the genetic algorithm, and then the distance-Doppler two-dimensional graph of the PD radar is obtained after distance ambiguity resolution and blind area compensation processing, and the result is shown in figure 3. In fig. 3, black represents a blind area, gray represents a detectable area, the abscissa is a velocity dimension, and the ordinate is a distance dimension. It can be seen from fig. 3 that after the optimal pulse repetition frequency group is searched by using the algorithm of the present invention, the other regions in the corresponding range-doppler two-dimensional map except the first blind region and the second blind region can achieve non-blind region detection. At this time, the optimal PRT groups are {242us,243us }, {269us,270us }, {311us,312us }, and {348us,349us }.
The simulation experiment shows that: according to the PD system radar clear image optimization method based on the genetic algorithm, the genetic algorithm is used for searching the optimal PRT group by using a 'repetition frequency' dithering method, the operation amount is reduced under the condition that the area of the clear image is ensured to be maximum, the working parameters of the radar are matched with the environment to the greatest extent, and the detection performance of the radar is improved.
Claims (5)
1. A PD radar pulse repetition frequency group selection method based on genetic algorithm is characterized in that a repeated frequency dithering method is used for calculating the fitness of a clear graph area obtained after distance ambiguity resolution and blind complementing processing, and the genetic algorithm is used for searching an optimal PRT group; the steps of the selection method include the following:
step 1, generating a PRT generating matrix meeting constraint conditions:
generating a PRT generation matrix of Q rows and W columns, wherein each row in the matrix represents a PRT group of a large pulse group, and elements of each row represent the PRT of each small pulse group in the large pulse group; each element in the PRT generator matrix is in the range [ T 1 ,T 2 ]In, satisfy p i(j+1) -p ij A = Δ condition; wherein Q is more than or equal to 100, the value of W is determined by the area requirement of the PD radar clear image, and T is 1 And T 2 The value of (A) is determined by the detection range of the PD radar, and the unit is mus, p i(j+1) Representing the value of the element, p, in the ith row and j +1 column of the PRT generator matrix ij The element values of the ith row and the jth column in the PRT generating matrix are represented, and when j is an odd number, delta =1 μ s;
step 2, calculating the adaptability value of each big pulse group after repeated frequency dithering:
step 2.1, determining the fitness value of each grid unit in the distance-Doppler two-dimensional graph of each small pulse group;
2.2, sequentially carrying out distance ambiguity resolution and blind compensation on each big pulse group by using a repetition frequency dithering method to obtain a distance-Doppler two-dimensional graph of the big pulse group after repetition frequency dithering, and calculating the fitness value of each big pulse group according to the fitness value of each grid unit in the distance-Doppler two-dimensional graph of each small pulse group;
step 3, adaptively updating the large pulse group in the PRT generating matrix through a genetic algorithm:
step 3.1, updating a PRT generating matrix by using a roulette algorithm;
step 3.2, performing cross operation on the large pulse group in the updated PRT generation matrix;
step 3.3, carrying out mutation operation on the large pulse group in the intersected PRT generating matrix;
step 4, judging whether the largest large pulse group in the fitness values in the PRT generating matrix which is updated by iteration for S times continuously is the same or not, wherein S is more than or equal to 5, if so, executing the step 5; otherwise, executing step 2;
and 5, outputting the large pulse group corresponding to the maximum fitness value in the PRT generating matrix.
2. The genetic algorithm-based PD radar pulse repetition frequency group selection method according to claim 1, characterized in that said calculating the fitness value of each group of large pulses in step 2.2 is given by:
wherein, C i Representing fitness values corresponding to the ith large pulse group, h is more than or equal to 1 and less than or equal to W, h is an odd number, a =0,1,2, a, N, b =0,1,2, a, M, W represents the total number of columns in a PRT generating matrix, N represents the total number of distance units of the distance-Doppler two-dimensional map of the ith large pulse group, M represents the total number of Doppler units of the distance-Doppler two-dimensional map of the ith large pulse group, c represents the total number of Doppler units of the distance-Doppler two-dimensional map of the ith large pulse group ih (a, b) denotes the fitness value of a grid cell consisting of the a-th range cell and the b-th Doppler cell in the h-th small pulse group of the ith large pulse group, c i(h+1) (a, b) represents the fitness value of the grid cell composed of the a-th range cell and the b-th Doppler cell in the h + 1-th small pulse group of the i-th large pulse group.
3. The genetic algorithm based PD radar pulse repetition frequency group selection method according to claim 2, characterized in that the step of updating the PRT generator matrix using roulette algorithm in step 3.1 is as follows:
first, the selection probability of each group of large pulses in the PRT generator matrix is calculated using the following formula:
wherein, F i Representing the selection probability of the ith big pulse group in the PRT generating matrix, and Q representing the total number of rows in the PRT generating matrix;
and secondly, sequentially selecting the V large pulse groups in the PRT generating matrix according to the selection probability by using a roulette algorithm, and sequentially replacing the large pulse groups with the low fitness from the high fitness in the V PRT generating matrices according to the selection sequence to obtain an updated PRT generating matrix.
4. The genetic algorithm-based PD radar pulse repetition frequency group selection method according to claim 1, characterized by the step 3.2 of interleaving the groups of large pulses in the updated PRT generator matrix:
step one, randomly selecting two large pulse groups k and l in an updated PRT generating matrix, and representing the two selected large pulse groups k and l into binary forms k 'and l';
second, randomly selecting one bit from k 'and l' expressed in binary form as the cross point of k 'and l', and taking all bits after the cross point of k 'and l' as the cross probability r c Performing cross operation to obtain the main pulse groups k 'and l', r after cross operation c Is in the range of [0.5,1]A value randomly selected in the range;
thirdly, judging whether the pulse repetition period of each small pulse group in the large pulse groups k 'and l' is in [ T ] 1 ,T 2 ]If yes, representing k 'and l' as decimal, replacing k and l in PRT generating matrix, and executing the fourth step; otherwise, executing the first step;
step four, judging whether the current cycle number is equal to Q, if so, executing the step five, otherwise, executing the step one;
and fifthly, finishing the cross operation of the big pulse group in the updated PRT generating matrix.
5. The PD radar pulse repetition frequency group selection method for genetic algorithms according to claim 1, characterized in that step 3.3 performs mutation operations on the group of large pulses in the interleaved PRT generator matrix:
step one, randomly selecting a large pulse group t from a PRT generating matrix after crossing, and representing the selected large pulse group t into a binary form t';
second, randomly selecting a bit in t 'expressed in binary form as the variation point of t', and inverting the bit of the variation point to varyThe probability of anomaly is r m Performing mutation to obtain a mutated aortic group t', r m Is in the range of [0,0.5 ]]A value is randomly selected in the range;
thirdly, judging whether the pulse repetition periods of all the small pulse groups in the big pulse group T' are all in [ T ] 1 ,T 2 ]If yes, representing t' as decimal, replacing t in PRT generating matrix, and executing the fourth step; otherwise, executing the first step;
step four, judging whether the current cycle number is equal to Q, if so, executing the step five; otherwise, executing the first step;
and fifthly, completing the variation operation of the large pulse group in the PRT generating matrix after the intersection.
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| CN116056158A (en) * | 2023-03-24 | 2023-05-02 | 新华三技术有限公司 | Frequency allocation method and device, electronic equipment and storage medium |
| CN117471449A (en) * | 2023-12-27 | 2024-01-30 | 中国电子科技集团公司第十四研究所 | Single group PD tracking method suitable for maneuvering target |
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| CN116056158A (en) * | 2023-03-24 | 2023-05-02 | 新华三技术有限公司 | Frequency allocation method and device, electronic equipment and storage medium |
| CN117471449A (en) * | 2023-12-27 | 2024-01-30 | 中国电子科技集团公司第十四研究所 | Single group PD tracking method suitable for maneuvering target |
| CN117471449B (en) * | 2023-12-27 | 2024-03-22 | 中国电子科技集团公司第十四研究所 | Single group PD tracking method suitable for maneuvering target |
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