A PRI estimation and pulse sequence extraction method and device

Abstract

The present invention provides a PRI estimation and pulse sequence extraction method and device, belonging to the field of radar signal sorting. The method comprises the following steps: obtaining a TOA sequence and a preset PRI value range of a pulse stream; calculating a PRI spectrum based on the TOA sequence, comparing the amplitude of the PRI spectrum with a detection threshold, and obtaining a potential set of non-jittered PRI values; segmenting the TOA sequence, calculating the amplitude of the PRI spectrum for each segment of data, and superimposing the PRI spectrum to obtain a segmented superimposed PRI spectrum, which is then compared with the detection threshold to obtain a potential set of jittered PRI values, and determining a current round of estimated PRI values ​​based on a PRI value identification criterion; and separating corresponding sequences of the estimated PRI values ​​using an improved DAG algorithm. The present invention accurately estimates potential PRI values ​​in a mixed radar signal based on the PRI spectrum, and the PRI spectrum has strong robustness against pulse omissions, false pulses, and noise uniformity, and has good adaptability to different types of PRIs.

Description

Technical Field

[0001] The present invention belongs to the field of radar signal sorting, and in particular relates to a PRI estimation and pulse sequence extraction method and device. Background Art

[0002] With the rapid development of radar technology, an increasing number of new radar systems are being widely deployed. This has led to increasingly complex pulse repetition interval (PRI) modulation in the signals intercepted by reconnaissance receivers. In addition to the fixed PRI commonly used in traditional radars, a variety of other PRI modulation schemes have emerged, including jittered PRI, staggered PRI, and sliding PRI. Furthermore, with the increasing complexity of the electromagnetic environment and the continuous advancement of countermeasures such as low probability of intercept (LPI) technology, hybrid radar pulse trains face not only severe pulse loss issues but also a large number of interfering pulses. Even pulse time of arrival (TOA) measurements can be affected by significant noise. These factors combine to significantly increase the difficulty and challenge of deinterleaving hybrid pulse trains.

[0003] Currently, radar signal sorting algorithms based on the PRI (Primary Interval) (PRI) mainly include the following: histogram algorithms, PRI transform algorithms, and period estimation algorithms. The histogram algorithm performs statistical analysis on the difference histograms of the pulse time of arrival (TOA) sequence at each level and estimates the pulse repetition interval (PRI) of the pulse sequence based on the statistical results. Pulse sequence retrieval techniques are then used to isolate the pulse sequence corresponding to the estimated PRI. The PRI transform algorithm estimates the PRI value of the pulse sequence by performing an autocorrelation transform on the TOA sequence. The period estimation algorithm converts the discrete TOA sequence into a periodic sequence whose period is proportional to the PRI value, using this as a basis for estimating the PRI value of the pulse sequence.

[0004] Among existing radar signal sorting methods, the PRI transform algorithm suppresses the frame period of complex repetition-rate modulated signals and is therefore unsuitable for sorting complex repetition-rate modulated signals. Histogram algorithms and period estimation methods are sensitive to PRI jitter and are therefore unsuitable for sorting jittered PRIs. Summary of the Invention

[0005] To address the above-mentioned deficiencies in the prior art, the present invention provides a method and apparatus for PRI estimation and pulse sequence extraction. Based on the PRI (Pulse Repetition Interval) spectrum and the Directed Acyclic Graph (DAG), the present invention addresses the problem that the prior art is unable to adapt to the deinterleaving of mixed pulse sequences.

[0006] The specific technical solution is: a PRI estimation and pulse sequence extraction method, which includes the following steps:

[0007] Step 1: Obtain the TOA sequence of the pulse stream and the preset PRI value range;

[0008] Step 2: Calculate the PRI spectrum based on the TOA sequence and compare the amplitude of the PRI spectrum with the detection threshold to obtain a set of potential non-dithered PRI values. If the set is empty, proceed to step 3. Otherwise, determine the estimated PRI value for this round based on the PRI value identification criterion and proceed to step 4.

[0009] Step 3: Segment the TOA sequence. Calculate the amplitude of the PRI spectrum for each segment and superimpose them to obtain the segmented superimposed PRI spectrum. This spectrum is then compared with the detection threshold to obtain a set of potential jitter PRI values. The estimated PRI value for this round is determined based on the PRI value identification criterion. If the set is empty, the algorithm terminates; otherwise, proceed to step 6.

[0010] Step 4: Based on the PRI value estimated in step 2, the improved DAG algorithm is used to separate the corresponding sequence. If the corresponding sequence is successfully separated, go to step 5; otherwise, go to step 3.

[0011] Step 5: Calculate the sub-pulse interval of the complex PRI modulation based on the estimated PRI value and the sequence retrieval result of the improved DAG algorithm to obtain the sub-PRI value. Then, if the number of remaining pulses is greater than the sorting threshold, go to step 2; otherwise, the algorithm ends.

[0012] Step 6: Based on the PRI value estimated in step 3, the improved DAG algorithm is used to separate the corresponding sequence. If the corresponding sequence is not successfully separated, the algorithm ends. If the corresponding sequence is successfully separated, it is determined whether the number of remaining pulses is greater than the sorting threshold. If it is greater than the sorting threshold, go to step 2 to start a new round of sorting; if it is less than the sorting threshold, the algorithm ends.

[0013] A PRI estimation and pulse sequence extraction device, comprising:

[0014] A TOA sequence and a preset PRI value range acquisition module is used to acquire the TOA sequence and the preset PRI value range of the pulse stream;

[0015] The PRI value estimation module calculates the PRI spectrum based on the TOA sequence and compares the amplitude of the PRI spectrum with the detection threshold to obtain a set of potential non-jitter PRI values. If the set is empty, the process proceeds to the segmented PRI value estimation module. Otherwise, the estimated PRI value for this round is determined based on the PRI value recognition criterion, and then the process proceeds to the sequence separation module.

[0016] The segmented PRI value estimation module segments the TOA sequence, calculates the amplitude of the PRI spectrum for each segment, and superimposes them to obtain the segmented superimposed PRI spectrum. This spectrum is then compared with the detection threshold to obtain a set of potential jitter PRI values. The estimated PRI value for this round is determined based on the PRI value identification criterion. If the set is empty, the algorithm terminates; otherwise, the algorithm proceeds to the remaining pulse number determination module.

[0017] The sequence separation module uses the improved DAG algorithm to separate the corresponding sequence according to the PRI value estimated by the PRI value estimation module. If the corresponding sequence is successfully separated, the module switches to the sub-PRI value calculation module; otherwise, the module switches to the segmented PRI value estimation module.

[0018] The sub-PRI value calculation module calculates the sub-pulse interval of the complex PRI modulation based on the estimated PRI value and the sequence retrieval result of the improved DAG algorithm to obtain the sub-PRI value. If the number of remaining pulses is greater than the sorting threshold, the module switches to the PRI value estimation module; otherwise, the algorithm ends.

[0019] The remaining pulse number judgment module uses the improved DAG algorithm to separate the corresponding sequence based on the PRI value estimated by the segmented PRI value estimation module. If the corresponding sequence is not successfully separated, the algorithm ends. If the corresponding sequence is successfully separated, it determines whether the remaining pulse number is greater than the sorting threshold. If it is greater than the sorting threshold, it switches to the PRI value estimation module to start a new round of sorting; if it is less than the sorting threshold, the algorithm ends.

[0020] An electronic device comprises: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors are enabled to implement the described method.

[0021] A computer-readable storage medium stores executable instructions, which, when executed by a processor, enable the processor to implement the method described above.

[0022] The present invention has the following beneficial effects:

[0023] 1. The present invention proposes a PRI spectrum, which can accurately estimate the potential PRI value in a mixed radar signal. The PRI spectrum is robust to pulse omissions, false pulses, and TOA measurement noise, and has good adaptability to different types of PRIs.

[0024] 2. This paper proposes a DAG-based pulse sequence retrieval method. By leveraging global information, the proposed pulse sequence retrieval algorithm achieves improved performance. Furthermore, for PRI sequences with complex modulation, the proposed sequence retrieval algorithm can retrieve all of their subsequences simultaneously, reducing the number of sorting rounds required.

[0025] 3. Based on the robustness of the PRI spectrum to pulse omissions, false pulses, and TOA measurement noise, as well as its adaptability to different types of PRIs, and the DAG's utilization of global information and reduction of sorting rounds, the proposed PRI spectrum and DAG-based PRI estimation and pulse train extraction method is adaptable to different types of PRIs and can maintain high accuracy and high speed in sorting mixed radar pulse trains in the presence of pulse omissions, false pulses, and TOA measurement noise. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 Flow chart of the method proposed in the present invention;

[0027] Figure 2 This is the first round of sorting PRI spectrum;

[0028] Figure 3 This is the second round of sorting PRI spectra;

[0029] Figure 4 This is the PRI spectrum for the third round of sorting;

[0030] Figure 5 This is the fourth round of sorting of unsegmented PRI spectra;

[0031] Figure 6 This is the segmented PRI spectrum for the first round of sorting;

[0032] Figure 7 This is the performance evaluation result graph of the merr indicator;

[0033] Figure 8 This is a graph showing the performance evaluation results of Prism metrics. DETAILED DESCRIPTION

[0034] To further clarify the objectives, technical solutions, and advantages of the present invention, the present invention is further described below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are intended solely to illustrate the present invention and are not intended to limit the present invention. Furthermore, the technical features described below in the various embodiments of the present invention may be combined as long as they do not conflict with one another. To achieve the aforementioned objectives, the present invention employs the following technical solutions. In the present invention, the PRI value stands for the Pulse Repetition Interval, which is used to describe the characteristics of radar signals. The PRI spectrum is a complex number calculated using the pulse arrival time (TOA) sequence to estimate the PRI value from the radar signal. The PRI amplitude spectrum is the modulus of the PRI spectrum, i.e., the amplitude of the PRI spectrum.

[0035] In order to achieve the above-mentioned purpose, the present invention provides a pulse sequence extraction method and device, the flow chart of which is as follows: Figure 1 As shown, the method includes:

[0036] Step 1: Obtain the TOA sequence of the pulse stream and the preset PRI value range;

[0037] Step 2: Calculate the PRI spectrum based on the TOA sequence and compare its amplitude with the detection threshold to obtain a set of potential non-dithered PRI values. If the set is empty, proceed to step 3. Otherwise, determine the estimated PRI value for this round based on the PRI value identification criteria and proceed to step 4.

[0038] In step 3, the TOA sequence is segmented. For each segment, the amplitude of the PRI spectrum is calculated and superimposed to obtain the segmented superimposed PRI spectrum. This spectrum is then compared with the detection threshold to obtain a set of potential jitter PRI values. The estimated PRI value for this round is determined based on the PRI value identification criteria. If the set is empty, the algorithm terminates. Otherwise, the process proceeds to step 6.

[0039] Step 4: Separate the corresponding sequence using the improved DAG algorithm based on the PRI value estimated in step 2. If the corresponding sequence is successfully separated, go to step 5; otherwise, go to step 3.

[0040] In step 5, based on the estimated PRI value and the sequence search results of the improved DAG algorithm, the sub-pulse interval of the complex PRI modulation is calculated to obtain the sub-PRI value. If the number of remaining pulses is greater than the sorting threshold, the algorithm proceeds to step 2; otherwise, the algorithm ends.

[0041] In step 6, based on the PRI value estimated in step 3, the improved DAG algorithm is used to separate the corresponding sequence. If the sequence is not separated successfully, the algorithm ends. If the sequence is separated successfully, the algorithm then determines whether the number of remaining pulses is greater than the sorting threshold. If so, the algorithm proceeds to step 2 to begin a new round of sorting. If not, the algorithm ends.

[0042] Furthermore, the step 1 comprises the following steps:

[0043] Step 1.1: Use simulation software to generate the TOA sequence of a pulse stream of a certain length or obtain the actual TOA sequence of the pulse stream by processing the received pulse stream through the signal acquisition system, and obtain the preset PRI value range and preset sampling interval. The TOA sequence model of the pulse stream is defined as:

[0044] ;

[0045] in, is the TOA sequence of the pulse stream, The first The arrival time of the pulses, is the number of pulses in the pulse stream.

[0046] Step 2 includes the following steps:

[0047] Step 2.1: Sample the preset PRI value range at the preset interval to obtain PRI candidate value, PRI candidate values for:

[0048] ;

[0049] in, For the above preset PRI value range, is the minimum PRI value, The maximum PRI value.

[0050] Step 2.2, calculate the PRI spectrum at the above PRI candidate values The value at :

[0051] ;

[0052] Step 2.3, calculate the detection threshold of the PRI spectrum according to the following formula;

[0053] ;

[0054] in, for The detection threshold at is an adjustable parameter, is a positive integer, The candidate value for the constant false alarm detector in PRI Output at is the duration of the pulse flow.

[0055] Step 2.4: add the PRI candidate values ​​whose PRI spectrum amplitude exceeds the detection threshold to the PRI candidate set :

[0056] ;

[0057] in, For the PRI values ​​to be selected, is the number of PRI values ​​to be selected;

[0058] Step 2.5, if If it is an empty set, jump to step 3; otherwise, traverse the set For each PRI candidate value in , select the PRI value corresponding to the peak with the largest ratio of the PRI spectrum amplitude to the detection threshold according to the following formula as the PRI value estimated in this round, and then jump to step 4:

[0059] ;

[0060] in, is the estimated PRI value for this round, , is the PRI value set corresponding to the PRI amplitude peak.

[0061] Step 3 includes the following steps:

[0062] Step 3.1, calculate the amplitude of the segmented PRI spectrum according to the following formula;

[0063] ;

[0064] in, is the segment length;

[0065] Step 3.2: Obtain the selected jitter PRI value set according to steps 2.3-2.4. ;

[0066] Step 3.3, if If it is an empty set, then end; otherwise, follow step 2.5 to get the estimated value of PRI for this round, and then jump to step 6.

[0067] Step 4: The improved DAG algorithm includes the following steps:

[0068] Step 4.1, construct DAG. Initialize the adjacency matrix of DAG as Then traverse the TOA of each pulse in the pulse sequence and all the subsequent pulses. If the first The pulse and pulses The TOA of the adjacency matrix satisfies the following relationship. OK Set the elements of the column to 1:

[0069] ;

[0070] in, and For the and The arrival time of the pulses, Used to determine the maximum value of the target pulse search range, The jitter upper limit of the PRI value.

[0071] Step 4.2: Traverse the adjacency matrix constructed in step 4.1 and find the nodes in the DAG with out-degree 0. For each node with out-degree 0, find the longest path ending at it.

[0072] Step 4.3: Among the paths in step 4.2, for paths starting from the same node, only the longest one is retained.

[0073] Step 4.4: Check the length of the longest path among the paths obtained in step 4.3. If its length is greater than the sequence retrieval threshold, sort the path lengths in ascending order; otherwise, jump back to step 3.

[0074] Step 4.5: Difference the lengths of the paths sorted in step 4.4. If the maximum difference value is greater than the path segmentation threshold, the path after the difference value is retained; otherwise, all paths are retained. Finally, a path set is obtained. , is the number of paths obtained, and then go to step 5.

[0075] The step 5 comprises the following steps:

[0076] Step 5.1, assume that in the path set obtained in step 4, The TOA contained in the path is ,in For the The length of the path. Then calculate the first The phase corresponding to each path is:

[0077] ;

[0078] ;

[0079] in, For the The value of the PRI spectrum of the path at the estimated PRI value, For the The phase corresponding to each path;

[0080] Step 5.2, Sort in ascending order, then Put it at the end of the sequence, then perform the difference to get the sub-PRI value of the complex pulse modulation.

[0081] ;

[0082] In step 5.3, check whether the number of remaining pulses is greater than the sorting threshold. If so, jump to step 2 and start a new round of sorting. Otherwise, the algorithm ends.

[0083] Step 6 comprises the following steps:

[0084] Step 6.1, build DAG according to step 4.1;

[0085] In step 6.2, find the longest path in the constructed DAG. If the path length is less than the sequence search threshold, the algorithm ends. Otherwise, separate the pulses corresponding to the path and determine whether the number of remaining pulses is greater than the sorting threshold. If so, jump to step 2 and start a new round of sorting; otherwise, the algorithm ends. Specific embodiments

[0087] In one example, the parameters of radar signal simulation are shown in Table 1. The simulation results are shown in Table 1. Figures 2 to 6 There are four rounds of sorting in this process. In the first round, 4 PRI values ​​exceeded the detection threshold. According to the cycle identification criteria, 285 This is the result of the first round of PRI identification; in the second round of sorting, 3 PRI values ​​exceeded the detection threshold. According to the cycle identification criterion, 370.8 This is the result of the second round of PRI recognition; in the third round of sorting, two PRI values ​​exceeded the detection threshold. According to the cycle recognition criterion, 524.9 This is the result of the third round of PRI recognition; in the fourth round, no PRI value of the unsegmented PRI spectrum exceeds the detection threshold, and one PRI value of the segmented PRI spectrum exceeds the detection threshold. According to the period recognition criterion, 524.9 The fourth round of PRI identification results is shown in Figure 2. The simulation results show that the proposed algorithm can complete PRI estimation and pulse sequence retrieval for mixed pulse sequences under the conditions of missing pulses, jitter, false pulses, and TOA measurement errors, and the PRI value estimation accuracy is very high.

[0088] In order to further verify the effectiveness of the present invention, the following two indicators are used to evaluate the performance of the algorithm:

[0089] ;

[0090] ;

[0091] in, is the PRI value estimated by the sorting algorithm, is the actual PRI value. is the number of true pulses in the results of sequence retrieval, is the number of interference pulses in the search sequence results, The number of real pulses that were not retrieved.

[0092] A mixed radar signal pulse stream is selected, and the parameters are shown in Table 2. The simulation results are shown in Figure 7 and Figure 8 It can be seen that when the pulse missing rate is 30%, the number of interference pulses is 200, and the jitter upper limit is 15%, the merr and prism of the present invention can reach 0.71% and 94.76% respectively.

[0093] Table 1 Example simulation parameters

[0094]

[0095] Table 2 Performance evaluation simulation parameters

[0096]

[0097] Another aspect of the present invention provides a PRI estimation and pulse sequence extraction device, comprising:

[0098] A TOA sequence and a preset PRI value range acquisition module is used to acquire the TOA sequence and the preset PRI value range of the pulse stream;

[0099] The PRI value estimation module calculates the PRI spectrum based on the TOA sequence and compares the amplitude of the PRI spectrum with the detection threshold to obtain a set of potential non-jitter PRI values. If the set is empty, the process proceeds to the segmented PRI value estimation module. Otherwise, the estimated PRI value for this round is determined based on the PRI value recognition criterion, and then the process proceeds to the sequence separation module.

[0100] The segmented PRI value estimation module segments the TOA sequence, calculates the amplitude of the PRI spectrum for each segment, and superimposes them to obtain the segmented superimposed PRI spectrum. This spectrum is then compared with the detection threshold to obtain a set of potential jitter PRI values. The estimated PRI value for this round is determined based on the PRI value identification criterion. If the set is empty, the algorithm terminates; otherwise, the algorithm proceeds to the remaining pulse number determination module.

[0101] The sequence separation module uses the improved DAG algorithm to separate the corresponding sequence according to the PRI value estimated by the PRI value estimation module. If the corresponding sequence is successfully separated, the module switches to the sub-PRI value calculation module; otherwise, the module switches to the segmented PRI value estimation module.

[0102] The sub-PRI value calculation module calculates the sub-pulse interval of the complex PRI modulation based on the estimated PRI value and the sequence retrieval result of the improved DAG algorithm to obtain the sub-PRI value. If the number of remaining pulses is greater than the sorting threshold, the module switches to the PRI value estimation module; otherwise, the algorithm ends.

[0103] The remaining pulse number judgment module uses the improved DAG algorithm to separate the corresponding sequence based on the PRI value estimated by the segmented PRI value estimation module. If the corresponding sequence is not successfully separated, the algorithm ends. If the corresponding sequence is successfully separated, it determines whether the remaining pulse number is greater than the sorting threshold. If it is greater than the sorting threshold, it switches to the PRI value estimation module to start a new round of sorting; if it is less than the sorting threshold, the algorithm ends.

[0104] Another aspect of the present invention provides an electronic device, comprising: one or more processors; and a memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors implement the described method.

[0105] Another aspect of the present invention provides a computer-readable storage medium having executable instructions stored thereon. When the instructions are executed by a processor, the processor is enabled to implement the method described above.

Claims

1. A PRI estimation and pulse sequence extraction method, characterized in that: The method comprises the following steps: Step 1: Obtain the TOA sequence of the pulse stream and the preset PRI value range; Step 2: Calculate the PRI spectrum based on the TOA sequence and compare the amplitude of the PRI spectrum with the detection threshold to obtain a set of potential non-dithered PRI values. If the set is empty, proceed to step 3. Otherwise, determine the estimated PRI value for this round based on the PRI value identification criterion and proceed to step 4. Step 3: Segment the TOA sequence. Calculate the amplitude of the PRI spectrum for each segment and superimpose them to obtain the segmented superimposed PRI spectrum. This spectrum is then compared with the detection threshold to obtain a set of potential jitter PRI values. The estimated PRI value for this round is determined based on the PRI value identification criterion. If the set is empty, the algorithm terminates; otherwise, proceed to step 6. Step 4: Based on the PRI value estimated in step 2, the improved DAG algorithm is used to separate the corresponding sequence. If the corresponding sequence is successfully separated, go to step 5; otherwise, go to step 3. Step 5: Calculate the sub-pulse interval of the complex PRI modulation based on the estimated PRI value and the sequence retrieval result of the improved DAG algorithm to obtain the sub-PRI value. Then, if the number of remaining pulses is greater than the sorting threshold, go to step 2; otherwise, the algorithm ends. Step 6: Based on the PRI value estimated in step 3, the improved DAG algorithm is used to separate the corresponding sequence. If the corresponding sequence is not successfully separated, the algorithm ends. If the corresponding sequence is successfully separated, it is determined whether the number of remaining pulses is greater than the sorting threshold. If it is greater than the sorting threshold, go to step 2 to start a new round of sorting; if it is less than the sorting threshold, the algorithm ends.

2. A PRI estimation and pulse sequence extraction method according to claim 1, characterized in that: The step 1 comprises the following steps: Step 1.1, the TOA sequence model of the pulse stream is defined as: ； in, is the TOA sequence of the pulse stream, The first The arrival time of the pulses, is the number of pulses in the pulse stream.

3. A PRI estimation and pulse sequence extraction method according to claim 2, characterized in that: Step 2 includes the following steps: Step 2.1: Sample the preset PRI value range at the preset interval to obtain PRI candidate value, PRI candidate values for: ； in, For the above preset PRI value range, is the minimum PRI value, is the maximum value of PRI; Step 2.2, calculate the PRI spectrum at the above PRI candidate values The value at : ； Step 2.3, calculate the detection threshold of the PRI spectrum according to the following formula; ； in, for The detection threshold at is an adjustable parameter, is a positive integer, The candidate value for the constant false alarm detector in PRI The output at is the duration of the pulse flow; Step 2.4: add the PRI candidate values ​​whose PRI spectrum amplitude exceeds the detection threshold to the PRI candidate set : ； in, For the PRI values ​​to be selected, is the number of PRI values ​​to be selected; Step 2.5, if If it is an empty set, jump to step 3; otherwise, traverse the set For each PRI candidate value in , select the PRI value corresponding to the peak with the largest ratio of the PRI spectrum amplitude to the detection threshold according to the following formula as the PRI value estimated in this round, and then jump to step 4: ； in, is the estimated PRI value for this round, , is the PRI value set corresponding to the PRI amplitude peak.

4. A PRI estimation and pulse sequence extraction method according to claim 3, characterized in that: Step 3 includes the following steps: Step 3.1, calculate the amplitude of the segmented PRI spectrum according to the following formula; ； in, is the segment length; Step 3.2: Obtain the selected jitter PRI value set according to steps 2.3-2.

4. ; Step 3.3, if If it is an empty set, then end; otherwise, follow step 2.5 to get the estimated value of PRI for this round, and then jump to step 6.

5. A PRI estimation and pulse sequence extraction method according to claim 4, characterized in that: In step 4 and step 6, the improved DAG algorithm includes the following steps: Step 4.1, construct DAG; including: initializing the adjacency matrix of DAG to Then traverse the TOA of each pulse in the pulse sequence and all the subsequent pulses. If the first The pulse and pulses The TOA of the adjacency matrix satisfies the following relationship. OK Set the elements of the column to 1: ； in, and For the and The arrival time of the pulses, Used to determine the maximum value of the target pulse search range, The jitter upper limit of the PRI value; Step 4.2: Traverse the adjacency matrix constructed in step 4.1 and find the nodes with out-degree 0 in the DAG. For each node with out-degree 0, find the longest path ending at it. Step 4.3: Among the paths in step 4.2, for those starting from the same node, only the longest one is retained; Step 4.4: Check the length of the longest path among the paths obtained in step 4.

3. If its length is greater than the sequence retrieval threshold, sort the path lengths in ascending order; otherwise, jump back to step 3. Step 4.5: Differencing the lengths of the paths sorted in step 4.

4. If the maximum difference value is greater than the path segmentation threshold, the path after the difference value is generated is retained; otherwise, all paths are retained, and a path set is finally obtained. , is the number of paths obtained, and then go to step 5.

6. A PRI estimation and pulse sequence extraction method according to claim 5, characterized in that: The step 5 comprises the following steps: Step 5.1, assume that in the path set obtained in step 4, The TOA contained in the path is ,in For the The length of the path is calculated according to the following formula The phase corresponding to each path is: ； ； in, For the The value of the PRI spectrum of the path at the estimated PRI value, For the The phase corresponding to each path; Step 5.2, Sort in ascending order, then Put it at the end of the sequence, then perform the difference to get the sub-PRI value of the complex pulse modulation; ； In step 5.3, check whether the number of remaining pulses is greater than the sorting threshold. If it is, jump to step 2 and start a new round of sorting. Otherwise, the algorithm ends.

7. A PRI estimation and pulse sequence extraction method according to claim 6, characterized in that: Step 6 comprises the following steps: Step 6.1, build DAG according to step 4.1; In step 6.2, the longest path in the constructed DAG is found. If the path length is less than the sequence retrieval threshold, the algorithm ends. Otherwise, the pulses corresponding to the path are separated, and the number of remaining pulses is determined to be greater than the sorting threshold. If so, jump to step 2 and start a new round of sorting; otherwise, the algorithm ends.

8. A PRI estimation and pulse sequence extraction device, characterized in that: include: A TOA sequence and a preset PRI value range acquisition module is used to acquire the TOA sequence and the preset PRI value range of the pulse stream; The PRI value estimation module calculates the PRI spectrum based on the TOA sequence, compares the amplitude of the PRI spectrum with the detection threshold, and obtains a set of potential non-jittered PRI values; If the set is empty, go to the segmented PRI value estimation module; Otherwise, the estimated PRI value of this round is determined according to the PRI value identification criterion, and then the process goes to the sequence separation module; The segmented PRI value estimation module segments the TOA sequence, calculates the amplitude of the PRI spectrum for each segment, and superimposes them to obtain the segmented superimposed PRI spectrum. This spectrum is then compared with the detection threshold to obtain a set of potential jitter PRI values. The estimated PRI value for this round is determined based on the PRI value identification criterion. If the set is empty, the algorithm terminates; otherwise, the algorithm proceeds to the remaining pulse number determination module. The sequence separation module uses the improved DAG algorithm to separate the corresponding sequence according to the PRI value estimated by the PRI value estimation module. If the corresponding sequence is successfully separated, it will turn to the sub-PRI value calculation module; Otherwise, go to the segmented PRI value estimation module; The sub-PRI value calculation module calculates the sub-pulse interval of the complex PRI modulation according to the estimated PRI value and the sequence retrieval result of the improved DAG algorithm to obtain the sub-PRI value. If the number of remaining pulses is greater than the sorting threshold, the module switches to the PRI value estimation module. Otherwise the algorithm ends; The remaining pulse number judgment module uses the improved DAG algorithm to separate the corresponding sequence according to the PRI value estimated by the segmented PRI value estimation module. If the corresponding sequence is not successfully separated, the algorithm ends. If the corresponding sequence is successfully separated, it determines whether the remaining pulse number is greater than the sorting threshold. If so, it switches to the PRI value estimation module to start a new round of sorting. If it is less than the sorting threshold, the algorithm ends.

9. An electronic device, characterized in that: include: one or more processors; A memory for storing one or more programs, wherein when the one or more programs are executed by the one or more processors, the one or more processors are enabled to implement the method according to any one of claims 1 to 7.

10. A computer-readable storage medium, characterized in that Executable instructions are stored thereon, and when the instructions are executed by a processor, the processor implements the method according to any one of claims 1 to 7.

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