A system and method for dynamic optimization of passive detection resource parameters based on spectrum monitoring

Abstract

The present invention discloses a system and method for dynamically optimizing passive detection resource parameters based on spectrum monitoring, which respectively controls spectrum monitoring resource resident parameters and passive detection resource resident parameters based on mission data, radar reception signals and spectrum monitoring data, and periodically optimizes passive detection resource resident parameters based on spectrum monitoring results and in combination with a spectrum knowledge base after receiving and processing radio frequency signals by a passive radar system. The dynamic optimization of passive detection resource parameters in the scheme of the present invention can customize search resource parameters according to the external environment to improve the probability of search and retention of intercepted targets; at the same time, when tracking the searched and intercepted targets, the tracking resource parameters and the tracking target parameters are dynamically adapted to improve the stability of target tracking.

Description

Technical Field

[0001] The invention belongs to the field of passive phased array radar resource scheduling, and in particular relates to a system and method for dynamically optimizing passive detection resource parameters based on spectrum monitoring. Background Art

[0002] As the modern electronic environment becomes more and more complex and changeable, the intelligence level of active radar is gradually improving, and modern scenarios have put forward higher requirements for radar reconnaissance. Traditional passive radars have difficulty achieving ideal performance due to their lack of adaptability to the real environment and the use of fixed working modes and scanning methods. How to improve the intelligence level of passive radars so that they can adapt to environmental changes and mission requirements has become a research topic that has received much attention in recent years. Against this background, cognitive radars came into being, providing a direction for the future intelligence of radars. As the control center of radars, resource scheduling can give full play to the characteristics of passive phased array radars by studying closed-loop scheduling algorithms for passive detection resources, so that they can adapt to environmental changes and mission requirements, which is crucial to improving the working efficiency of the entire phased array radar.

[0003] Most existing passive phased arrays mainly study adaptive scheduling algorithms. For example, some existing technologies use comprehensive priority algorithms to achieve adaptive scheduling of tasks, design evaluation functions for scheduling benefits and scheduling costs, and improve the ability of multi-task comprehensive scheduling; some analyze the prior knowledge of a large number of passive radar tasks, dynamically match tasks with radar system resources, and focus on solving the problem of task congestion; and some accumulate the radiation intensity values ​​intercepted by key radiation source targets within different angle ranges to identify the area where the target appears, thereby adaptively adjusting the radar fan scanning center and fan scanning range.

[0004] The closed-loop scheduling algorithm for radar system resources with cognitive functions is mainly aimed at active radars, or by adjusting the transmission waveform to effectively avoid the interference spectrum to improve the radar's anti-interference ability, or by selecting radar waveform parameters based on environmental perception to achieve performance optimization of maneuvering target detection and tracking in a cluttered environment. For example, some existing technologies combine the closed-loop working characteristics of cognitive tracking radars to study their optimal tracking waveform design under the background of related clutter. Some start from the cognitive radar architecture, further optimize the cognitive radar architecture, and explain the concept and necessity of cognitive radar parameterization; starting from the radar equation, combined with the general scheduling requirements of cognitive radar, determine the structure and specific parameters of the parameterized waveform, and establish a complete parameterized waveform.

[0005] The above technology mainly focuses on dynamic optimization of active detection resource parameters. There is a lack of research on the dynamic optimization algorithm of passive detection resource parameters in the existing technology. The passive detection resource parameters are fixed, and its search resource parameters cannot be customized according to the environment, resulting in a low probability of searching and intercepting the target. At the same time, when tracking the searched and intercepted target, the tracking resource parameters and the tracking target parameters are mismatched, and the target is easily lost. Summary of the invention

[0006] In view of the above problems, the object of the present invention is to provide a system and method for dynamic optimization of passive detection resource parameters based on spectrum monitoring.

[0007] The specific technical solution for achieving the purpose of the present invention is:

[0008] A passive detection resource parameter dynamic optimization system based on spectrum monitoring, comprising a task scheduling module, a spectrum monitoring module, a radio frequency receiving module and a beam control module;

[0009] The task scheduling module controls the spectrum monitoring resource resident parameters and the passive detection resource resident parameters respectively based on the task data, the radar receiving signal and the spectrum monitoring data of the spectrum monitoring module, and realizes the reception and processing of the radio frequency signal by the passive radar system through the beam control module and the radio frequency receiving module;

[0010] The spectrum monitoring module processes the radio frequency signal to generate a spectrum monitoring result, and periodically transmits it to the task scheduling module. The task scheduling module dynamically optimizes the passive detection resource resident parameters based on the spectrum monitoring result and in combination with the spectrum knowledge base.

[0011] Further, the passive detection resource residency parameters include passive search resource residency parameters and passive tracking resource residency parameters;

[0012] When the task scheduling module receives a passive search task, it dynamically optimizes the passive search resource resident parameters based on the spectrum monitoring data and the spectrum knowledge base;

[0013] When the target to be tracked is searched or a passive tracking task is received, the task scheduling module dynamically optimizes the passive tracking resource resident parameters based on the spectrum monitoring data and the spectrum knowledge base.

[0014] Furthermore, the process of optimizing the passive search resource resident parameters is as follows:

[0015] Based on the received passive search task data, the search area is divided into cells according to the instantaneous bandwidth and instantaneous azimuth coverage;

[0016] At certain time intervals, the dwell start time, dwell duration, and dwell frequency parameters are sent to the beam control module. The beam control module generates control parameters and sends them to the RF receiving module. After receiving the RF data, the RF receiving module sends them to the spectrum monitoring module.

[0017] Receive the spectrum monitoring results generated by the spectrum monitoring module, and calculate the amplitude accumulation value of the corresponding cell and the average of the amplitude accumulation values ​​of all cells based on the azimuth-frequency-amplitude statistical information in the spectrum monitoring results of the current scheduling period and the spectrum knowledge base;

[0018] The cells are searched and retained in order from large to small according to the amplitude accumulation value. For grids with amplitude accumulation values ​​less than or equal to the mean, they are retained according to the initial retention time; for grids with amplitude accumulation values ​​greater than the mean, the retention time is increased to n times the initial retention time; for grids with amplitude accumulation values ​​of zero, no search and retention is performed, completing the optimization of passive search resource retention parameters.

[0019] Furthermore, the amplitude accumulation value of the corresponding cell is:

[0020] ;

[0021] in is the amplitude of the nth spectrum point, is the minimum amplitude that the radar can detect, is the influence of the frequency corresponding to the nth spectrum point, which is obtained by searching the spectrum knowledge base. is the number of spectrum points in each cell;

[0022] The mean of the accumulated values ​​of all cell amplitudes is:

[0023] ;

[0024] in, is the total number of cells, The accumulated value of the amplitude of the mth cell.

[0025] Furthermore, the process of optimizing the passive tracking resource resident parameters is as follows:

[0026] Before the task scheduling module receives spectrum monitoring results of sufficient duration, tracking and retention are performed according to the radar detection target update period data rate, and the retention duration is fixed; when the task scheduling module receives spectrum monitoring results of sufficient duration, the passive tracking resource retention parameters are dynamically optimized according to the spectrum monitoring results, namely:

[0027] The most recent period of time is used as the statistical period, and the spectrum points of the tracking task frequency are selected from the time-frequency-amplitude statistical information of the spectrum monitoring results. The frequency tolerance is set to the radar frequency measurement accuracy.

[0028] When the task frequency is , the radar frequency measurement accuracy is , then the frequency of the selected spectrum Need to meet: ;

[0029] If the maximum amplitude among the selected spectrum points is , then select the amplitude value from -a to The spectrum points are sorted from small to large according to the arrival time, and the arrival time of adjacent spectrum points is subtracted;

[0030] When the difference in arrival time between adjacent spectrum points is greater than a certain time, it is considered that the next scan of the detection target starts from this spectrum point, so the spectrum points are divided into different clusters;

[0031] Then, b spectrum points with the largest amplitude are selected from each cluster and the mean arrival time is calculated;

[0032] Subtract the mean arrival time of each cluster and calculate the mean of the time difference to get the scanning period of the tracking target;

[0033] Scan cycle Track and reside for data rate, and determine the residency duration and the residency start time, so as to complete the optimization of passive tracking resource residency parameters.

[0034] Furthermore, the dwell time must be greater than the search dwell time;

[0035] The dwell start time of the tracking target for:

[0036]

[0037] Where n is the minimum value of N that satisfies the following formula:

[0038]

[0039] is the arrival time of the last spectrum point cluster of the target, represents the current time, p represents the scheduling time slice, and N is the intermediate parameter.

[0040] The present invention also provides a method for dynamically optimizing passive detection resource parameters based on spectrum monitoring, which is applied to the above system and includes the following steps:

[0041] Step 1: The task scheduling module controls the spectrum monitoring resource resident parameters and the passive detection resource resident parameters respectively based on the task data, the radar receiving signal and the spectrum monitoring data of the spectrum monitoring module;

[0042] Step 2: The beam control module and the RF receiving module perform radar detection beam control based on the dwell parameters and receive RF signals;

[0043] Step 3: The spectrum monitoring module processes the radio frequency signal to generate spectrum monitoring results, and periodically transmits them to the task scheduling module;

[0044] Step 4: The task scheduling module dynamically optimizes the passive detection resource retention parameters based on the spectrum monitoring results and the spectrum knowledge base, and returns to step 1.

[0045] Compared with the prior art, the present invention has the following beneficial effects:

[0046] The scheme of the present invention forms a closed-loop scheduling loop by combining modules such as task scheduling, spectrum monitoring, beam control, and radio frequency reception. The task scheduling periodically receives the spectrum monitoring results output by the spectrum monitoring, and combines the spectrum knowledge base to realize dynamic optimization of the resident parameters of passive detection resources. The scheme of the present invention enables the passive phased array radar to have the ability to adapt to the real environment, solves the problem of resource waste caused by the fixed scanning mode and tracking mode of the traditional passive phased array radar, and improves the resource utilization rate of radar target detection.

[0047] The passive detection resource parameters of the solution of the present invention are dynamically optimized, and the search resource parameters can be customized according to the external environment to improve the probability of searching, retaining and intercepting the target; at the same time, when tracking the searched and intercepted target, the tracking resource parameters and the tracking target parameters are dynamically adapted to improve the target tracking stability.

[0048] The present invention is further described below in conjunction with specific implementation modes. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of the architecture of the system for dynamic optimization of passive detection resource parameters based on spectrum monitoring of the present invention.

[0050] Figure 2 It is a schematic diagram of the dynamic optimization process of passive search resource parameters of the present invention.

[0051] Figure 3 It is a schematic diagram of the dynamic optimization process of passive tracking resource parameters of the present invention.

[0052] Figure 4 It is a schematic diagram of azimuth-frequency-amplitude monitoring data in an embodiment of the present invention.

[0053] Figure 5 Schematic diagram of time-frequency-amplitude monitoring data in an embodiment of the present invention. DETAILED DESCRIPTION

[0054] Example

[0055] The technical solutions in the embodiments of the present invention will be described clearly and completely below in conjunction with the accompanying drawings in the embodiments of the present invention. The described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0056] As shown in this application and claims, unless the context clearly indicates an exception, the words "a", "an", "an kind" and / or "the" do not refer to the singular and may also include the plural. Generally speaking, the terms "include" and "comprise" only indicate the inclusion of the steps and elements that have been clearly identified, and these steps and elements do not constitute an exclusive list. The method or device may also include other steps or elements.

[0057] Unless otherwise specifically stated, the relative arrangement, numerical expressions and numerical values ​​of the parts and steps set forth in these embodiments do not limit the scope of the present application. At the same time, it should be understood that, for ease of description, the sizes of the various parts shown in the accompanying drawings are not drawn according to the actual proportional relationship. The technology, method and equipment known to those of ordinary skill in the relevant field may not be discussed in detail, but in appropriate cases, the technology, method and equipment should be considered as a part of the authorization specification. In all examples shown and discussed here, any specific value should be interpreted as being merely exemplary, rather than as a limitation. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters represent similar items in the following drawings, so that once a certain item is defined in an accompanying drawing, it does not need to be further discussed in subsequent drawings.

[0058] Combination Figure 1 , a passive detection resource parameter dynamic optimization system based on spectrum monitoring, including a task scheduling module, a spectrum monitoring module, a radio frequency receiving module and a beam control module;

[0059] The task scheduling module periodically receives the spectrum monitoring results output by the spectrum monitoring, controls the spectrum monitoring resource resident parameters and the passive detection resource resident parameters respectively based on the task data, the radar receiving signal and the spectrum monitoring data of the spectrum monitoring module, and realizes the reception and processing of the radio frequency signal by the passive radar system through the beam control module and the radio frequency receiving module;

[0060] The spectrum monitoring module processes the radio frequency signal to generate a spectrum monitoring result, and periodically transmits it to the task scheduling module. The task scheduling module dynamically optimizes the passive detection resource resident parameters based on the spectrum monitoring result and in combination with the spectrum knowledge base.

[0061] The spectrum monitoring results include the current passive phased array radar surrounding environment or radiation source target’s azimuth-frequency-amplitude, time-frequency-amplitude and other statistical information;

[0062] The spectrum knowledge base includes: spectrum data stored in terms of influence, represented as influence-frequency value, or influence-frequency range.

[0063] In this embodiment, the scheduling time slice is 50ms, the initial dwell time of the search task is 50ms, the dwell time of a single frequency point of spectrum monitoring is 5ms, and the radar detection target scanning cycle ranges from 1s to 10s.

[0064] The passive detection resource resident parameters include passive search resource resident parameters and passive tracking resource resident parameters;

[0065] When the task scheduling module receives a passive search task, it dynamically optimizes the passive search resource resident parameters based on the spectrum monitoring data and the spectrum knowledge base;

[0066] When the target to be tracked is searched or a passive tracking task is received, the task scheduling module dynamically optimizes the passive tracking resource resident parameters based on the spectrum monitoring data and the spectrum knowledge base.

[0067] Specifically, the entire closed-loop workflow is:

[0068] The radar is turned on, the display control sets the search scanning area and frequency range, and the passive search task is sent to the task scheduler;

[0069] Task scheduling controls the spectrum monitoring dwell start time, dwell frequency, dwell duration and other dwell parameters at 50ms intervals: each scheduling time slice arranges 10 frequency point spectrum monitoring tasks, the dwell duration is fixed at 5ms, and the dwell frequency is from the starting frequency To end frequency Cycle scanning, is the total frequency points, assuming that the starting time of the scheduling time slice is , then the starting time of each task residence is:

[0070]

[0071] Task scheduling sends the resident parameters to beam control, beam control generates control parameters and sends them to RF reception, and RF reception receives RF data and sends it to spectrum monitoring;

[0072] The spectrum monitoring processes the RF data to generate spectrum monitoring results, including the azimuth-frequency-amplitude and time-frequency-amplitude statistics of the current passive phased array radar surrounding environment or radiation source target, as shown in the figure below. Figure 4 and Figure 5 As shown, it is sent to task scheduling;

[0073] Before the task scheduler receives the panoramic spectrum monitoring results, that is, before the spectrum monitoring completes the scanning of the entire airspace and the entire frequency band, the search task is dwelled in ascending order of frequency points at intervals of 50ms, and the dwell time is fixed at 50ms;

[0074] After receiving the panoramic spectrum monitoring results, the task scheduler dynamically optimizes the passive search resource resident parameters at 50ms intervals, including the following processes: Figure 2 As shown:

[0075] Based on the received passive search task data, the search area is divided into cells according to the instantaneous bandwidth and instantaneous azimuth coverage;

[0076] At certain time intervals, the dwell start time, dwell duration, and dwell frequency parameters are sent to the beam control module. The beam control module generates control parameters and sends them to the RF receiving module. After receiving the RF data, the RF receiving module sends them to the spectrum monitoring module.

[0077] Receive the spectrum monitoring results generated by the spectrum monitoring module, and calculate the amplitude accumulation value of the corresponding cell and the mean of the amplitude accumulation values ​​of all cells based on the azimuth-frequency-amplitude statistical information in the spectrum monitoring results of the current scheduling period and the spectrum knowledge base:

[0078] The accumulated amplitude value of the corresponding cell is:

[0079] ;

[0080] in is the amplitude of the nth spectrum point, is the minimum amplitude that the radar can detect, is the influence of the frequency corresponding to the nth spectrum point, which is obtained by searching the spectrum knowledge base. is the number of spectrum points in each cell;

[0081] The mean of the accumulated values ​​of all cell amplitudes is:

[0082] ;

[0083] in, is the total number of cells, The accumulated value of the amplitude of the mth cell.

[0084] The cells are searched and retained in order from large to small according to the amplitude accumulation value. For grids with amplitude accumulation values ​​less than or equal to the mean, they are retained according to the set initial retention time of 50ms; for grids with amplitude accumulation values ​​greater than the mean, the retention time is increased to n times the initial retention time, such as twice 100ms; for grids with amplitude accumulation values ​​of zero, no search and retention is performed, completing the optimization of passive search resource retention parameters.

[0085] Combination Figure 3 The process of optimizing the passive tracking resource residency parameters is as follows:

[0086] Before the task scheduling module receives spectrum monitoring results of sufficient duration, that is, before receiving spectrum monitoring results of three times the maximum scanning period of the radar detection target (30s in this embodiment), tracking and resident are performed according to the radar detection target update period data rate, and the resident duration is fixed at 1000ms; after the task scheduling receives spectrum monitoring results of sufficient duration, that is, after 30s, the passive tracking resource resident parameters are dynamically optimized according to the spectrum monitoring results, that is:

[0087] The most recent period of time, i.e. 30 seconds, is used as the statistical duration. The spectrum points of the tracking task frequency are selected from the time-frequency-amplitude statistical information of the spectrum monitoring results. The frequency tolerance is set to the radar frequency measurement accuracy.

[0088] The basis for selecting spectrum points is: when the task frequency is , the radar frequency measurement accuracy is , then the frequency of the selected spectrum Need to meet: ;

[0089] If the maximum amplitude among the selected spectrum points is , then select the amplitude value from -10 to The spectrum points are sorted from small to large according to the arrival time, and the arrival time of adjacent spectrum points is subtracted;

[0090] When the difference in arrival time between adjacent spectrum points is greater than a certain time, such as 1s, it is considered that the next scan of the detection target starts from this spectrum point. This method is used to divide the spectrum points into different clusters, such as Figure 5 As shown, it includes 3 spectral point clusters;

[0091] Then, 10 spectrum points with the largest amplitude are selected from each cluster and the mean arrival time is calculated;

[0092] Subtract the mean arrival time of each cluster and calculate the mean of the time difference to get the scanning period of the tracking target;

[0093] Scan cycle Track and reside for data rate, and determine the residency duration and the residency start time, so as to complete the optimization of passive tracking resource residency parameters.

[0094] The dwell time must be greater than the search dwell time. In this embodiment, the target tracking dwell time is set to 4 times the scheduling time slice, which can also be modified according to actual conditions.

[0095] The dwell start time of the tracking target for:

[0096]

[0097] Where n is the minimum value of N that satisfies the following formula:

[0098]

[0099] is the arrival time of the last spectrum point cluster of the target, Indicates the current time of resource scheduling (ms), p indicates the scheduling time slice, and N is an intermediate parameter with no actual meaning.

[0100] The present invention also provides a method for dynamically optimizing passive detection resource parameters based on spectrum monitoring based on the above system, comprising the following steps:

[0101] Step 1: The task scheduling module controls the spectrum monitoring resource resident parameters and the passive detection resource resident parameters respectively based on the task data, the radar receiving signal and the spectrum monitoring data of the spectrum monitoring module;

[0102] Step 2: The beam control module and the RF receiving module perform radar detection beam control based on the dwell parameters and receive RF signals;

[0103] Step 3: The spectrum monitoring module processes the radio frequency signal to generate spectrum monitoring results, and periodically transmits them to the task scheduling module;

[0104] Step 4: The task scheduling module dynamically optimizes the passive detection resource retention parameters based on the spectrum monitoring results and the spectrum knowledge base, and returns to step 1.

[0105] Among them, the dynamic optimization of passive detection resource resident parameters includes the optimization of passive search resource resident parameters and the optimization of passive tracking resource resident parameters;

[0106] When the task scheduling module receives a passive search task, it dynamically optimizes the passive search resource resident parameters based on the spectrum monitoring data and the spectrum knowledge base;

[0107] When the target to be tracked is searched or a passive tracking task is received, the task scheduling module dynamically optimizes the passive tracking resource resident parameters based on the spectrum monitoring data and the spectrum knowledge base.

[0108] The passive search resource resident parameter optimization is specifically as follows:

[0109] Based on the received passive search task data, the search area is divided into cells according to the instantaneous bandwidth and instantaneous azimuth coverage;

[0110] At certain time intervals, the dwell start time, dwell duration, and dwell frequency parameters are sent to the beam control module. The beam control module generates control parameters and sends them to the RF receiving module. After receiving the RF data, the RF receiving module sends them to the spectrum monitoring module.

[0111] Receive the spectrum monitoring results generated by the spectrum monitoring module, and calculate the amplitude accumulation value of the corresponding cell and the mean of the amplitude accumulation values ​​of all cells based on the azimuth-frequency-amplitude statistical information in the spectrum monitoring results of the current scheduling period and the spectrum knowledge base:

[0112] The accumulated amplitude value of the corresponding cell is:

[0113] ;

[0114] in is the amplitude of the nth spectrum point, is the minimum amplitude that the radar can detect, is the influence of the frequency corresponding to the nth spectrum point, which is obtained by searching the spectrum knowledge base. is the number of spectrum points in each cell;

[0115] The mean of the accumulated values ​​of all cell amplitudes is:

[0116] ;

[0117] in, is the total number of cells, is the accumulated value of the amplitude of the mth cell;

[0118] The cells are searched and retained in order from large to small according to the amplitude accumulation value. For grids with amplitude accumulation values ​​less than or equal to the mean, they are retained according to the initial retention time; for grids with amplitude accumulation values ​​greater than the mean, the retention time is increased to n times the initial retention time; for grids with amplitude accumulation values ​​of zero, no search and retention is performed, completing the optimization of passive search resource retention parameters.

[0119] The passive tracking resource resident parameter optimization is specifically as follows:

[0120] Before the task scheduling module receives spectrum monitoring results of sufficient duration, tracking and retention are performed according to the radar detection target update period data rate, and the retention duration is fixed; when the task scheduling module receives spectrum monitoring results of sufficient duration, the passive tracking resource retention parameters are dynamically optimized according to the spectrum monitoring results, namely:

[0121] The most recent period of time is used as the statistical period, and the spectrum points of the tracking task frequency are selected from the time-frequency-amplitude statistical information of the spectrum monitoring results. The frequency tolerance is set to the radar frequency measurement accuracy.

[0122] When the task frequency is , the radar frequency measurement accuracy is , then the frequency of the selected spectrum Need to meet: ;

[0123] If the maximum amplitude among the selected spectrum points is , then select the amplitude value from -a to The spectrum points are sorted from small to large according to the arrival time, and the arrival time of adjacent spectrum points is subtracted;

[0124] When the difference in arrival time between adjacent spectrum points is greater than a certain time, it is considered that the next scan of the detection target starts from this spectrum point. This method is used to divide the spectrum points into different clusters.

[0125] Then, b spectrum points with the largest amplitude are selected from each cluster and the mean arrival time is calculated;

[0126] Subtract the mean arrival time of each cluster and calculate the mean of the time difference to get the scanning period of the tracking target;

[0127] Scan cycle Track and retain data rates, and determine retention duration and retention start time, thereby optimizing retention parameters of passive tracking resources;

[0128] The dwell time must be greater than the search dwell time.

[0129] The dwell start time of the tracking target for:

[0130]

[0131] Where n is the minimum value of N that satisfies the following formula:

[0132]

[0133] is the arrival time of the last spectrum point cluster of the target, Represents the current time, p represents the scheduling time slice, and N is an intermediate parameter with no actual meaning.

[0134] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the invention patent. It should be pointed out that, for a person of ordinary skill in the art, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application. Therefore, the protection scope of the patent of the present application shall be subject to the attached claims.

Claims

1. A passive detection resource parameter dynamic optimization system based on spectrum monitoring, characterized in that: It includes task scheduling module, spectrum monitoring module, RF receiving module and beam control module; The task scheduling module controls the spectrum monitoring resource resident parameters and the passive detection resource resident parameters respectively based on the task data, the radar receiving signal and the spectrum monitoring data of the spectrum monitoring module, and realizes the reception and processing of the radio frequency signal by the passive radar system through the beam control module and the radio frequency receiving module; The spectrum monitoring module processes the radio frequency signal to generate spectrum monitoring results, and periodically transmits them to the task scheduling module. The task scheduling module dynamically optimizes the passive detection resource resident parameters based on the spectrum monitoring results and in combination with the spectrum knowledge base. The passive detection resource resident parameters include passive search resource resident parameters and passive tracking resource resident parameters; When the task scheduling module receives a passive search task, it dynamically optimizes the passive search resource resident parameters based on the spectrum monitoring data and the spectrum knowledge base; When the target to be tracked is searched or a passive tracking task is received, the task scheduling module dynamically optimizes the passive tracking resource resident parameters based on the spectrum monitoring data and the spectrum knowledge base.

2. The system for dynamic optimization of passive detection resource parameters based on spectrum monitoring according to claim 1, characterized in that: The process of optimizing the passive search resource resident parameters is as follows: Based on the received passive search task data, the search area is divided into cells according to the instantaneous bandwidth and instantaneous azimuth coverage; At certain time intervals, the dwell start time, dwell duration, and dwell frequency parameters are sent to the beam control module. The beam control module generates control parameters and sends them to the RF receiving module. After receiving the RF data, the RF receiving module sends them to the spectrum monitoring module. Receive the spectrum monitoring results generated by the spectrum monitoring module, and calculate the amplitude accumulation value of the corresponding cell and the average of the amplitude accumulation values ​​of all cells based on the azimuth-frequency-amplitude statistical information in the spectrum monitoring results of the current scheduling period and the spectrum knowledge base; The cells are searched and retained in order from large to small according to the amplitude accumulation value. For grids with amplitude accumulation values ​​less than or equal to the mean, they are retained according to the initial retention time; for grids with amplitude accumulation values ​​greater than the mean, the retention time is increased to n times the initial retention time; for grids with amplitude accumulation values ​​of zero, no search and retention is performed, completing the optimization of passive search resource retention parameters.

3. The system for dynamic optimization of passive detection resource parameters based on spectrum monitoring according to claim 2, characterized in that: The accumulated amplitude value of the corresponding cell is: ； in is the amplitude of the nth spectrum point, is the minimum amplitude that the radar can detect, is the influence of the frequency corresponding to the nth spectrum point, which is obtained by searching the spectrum knowledge base. is the number of spectrum points in each cell; The mean of the accumulated values ​​of all cell amplitudes is: ； in, is the total number of cells, The accumulated value of the amplitude of the mth cell.

4. The system for dynamic optimization of passive detection resource parameters based on spectrum monitoring according to claim 1, characterized in that: The process of optimizing the passive tracking resource resident parameters is as follows: Before the task scheduling module receives spectrum monitoring results of sufficient duration, tracking and retention are performed according to the radar detection target update period data rate, and the retention duration is fixed; when the task scheduling module receives spectrum monitoring results of sufficient duration, the passive tracking resource retention parameters are dynamically optimized according to the spectrum monitoring results, namely: The most recent period of time is used as the statistical period, and the spectrum points of the tracking task frequency are selected from the time-frequency-amplitude statistical information of the spectrum monitoring results. The frequency tolerance is set to the radar frequency measurement accuracy. When the task frequency is , the radar frequency measurement accuracy is , then the frequency of the selected spectrum Need to meet: ; If the maximum amplitude among the selected spectrum points is , then select the amplitude value from -a to The spectrum points are sorted from small to large according to the arrival time, and the arrival time of adjacent spectrum points is subtracted; When the difference in arrival time between adjacent spectrum points is greater than a certain time, it is considered that the next scan of the detection target starts from this spectrum point, so the spectrum points are divided into different clusters; Then, b spectrum points with the largest amplitude are selected from each cluster and the mean arrival time is calculated; Subtract the mean arrival time of each cluster and calculate the mean of the time difference to get the scanning period of the tracking target; Scan cycle Track and reside for data rate, and determine the residency duration and the residency start time, so as to complete the optimization of passive tracking resource residency parameters.

5. The system for dynamic optimization of passive detection resource parameters based on spectrum monitoring according to claim 4 is characterized in that: The dwell time must be greater than the search dwell time; The dwell start time of the tracking target for: ； Where n is the minimum value of N that satisfies the following formula: ； is the arrival time of the last spectrum point cluster of the target, represents the current time, p represents the scheduling time slice, and N is the intermediate parameter.

6. A method for dynamic optimization of passive detection resource parameters based on spectrum monitoring, applied to the system described in claim 1, characterized in that: The following steps are involved: Step 1: The task scheduling module controls the spectrum monitoring resource resident parameters and the passive detection resource resident parameters respectively based on the task data, the radar receiving signal and the spectrum monitoring data of the spectrum monitoring module; Step 2: The beam control module and the RF receiving module perform radar detection beam control based on the resident parameters and receive RF signals; Step 3: The spectrum monitoring module processes the radio frequency signal to generate spectrum monitoring results, and periodically transmits them to the task scheduling module; Step 4: The task scheduling module dynamically optimizes the passive detection resource retention parameters based on the spectrum monitoring results and the spectrum knowledge base, and returns to step 1; The passive detection resource resident parameter dynamic optimization includes passive search resource resident parameter optimization and passive tracking resource resident parameter optimization; When the task scheduling module receives a passive search task, it dynamically optimizes the passive search resource resident parameters based on the spectrum monitoring data and the spectrum knowledge base; When the target to be tracked is searched or a passive tracking task is received, the task scheduling module dynamically optimizes the passive tracking resource resident parameters based on the spectrum monitoring data and the spectrum knowledge base.

7. The method for dynamic optimization of passive detection resource parameters based on spectrum monitoring according to claim 6, characterized in that: The passive search resource resident parameter optimization is specifically as follows: Based on the received passive search task data, the search area is divided into cells according to the instantaneous bandwidth and instantaneous azimuth coverage; At certain time intervals, the dwell start time, dwell duration, and dwell frequency parameters are sent to the beam control module. The beam control module generates control parameters and sends them to the RF receiving module. After receiving the RF data, the RF receiving module sends them to the spectrum monitoring module. Receive the spectrum monitoring results generated by the spectrum monitoring module, and calculate the amplitude accumulation value of the corresponding cell and the mean of the amplitude accumulation values ​​of all cells based on the azimuth-frequency-amplitude statistical information in the spectrum monitoring results of the current scheduling period and the spectrum knowledge base: The accumulated amplitude value of the corresponding cell is: ； in is the amplitude of the nth spectrum point, is the minimum amplitude that the radar can detect, is the influence of the frequency corresponding to the nth spectrum point, which is obtained by searching the spectrum knowledge base. is the number of spectrum points in each cell; The mean of the accumulated values ​​of all cell amplitudes is: ； in, is the total number of cells, is the accumulated value of the amplitude of the mth cell; The cells are searched and retained in order from large to small according to the amplitude accumulation value. For grids with amplitude accumulation values ​​less than or equal to the mean, they are retained according to the initial retention time; for grids with amplitude accumulation values ​​greater than the mean, the retention time is increased to n times the initial retention time; for grids with amplitude accumulation values ​​of zero, no search and retention is performed, completing the optimization of passive search resource retention parameters.

8. The method for dynamic optimization of passive detection resource parameters based on spectrum monitoring according to claim 6, characterized in that: The passive tracking resource resident parameter optimization is specifically as follows: Before the task scheduling module receives spectrum monitoring results of sufficient duration, tracking and retention are performed according to the radar detection target update period data rate, and the retention duration is fixed; when the task scheduling module receives spectrum monitoring results of sufficient duration, the passive tracking resource retention parameters are dynamically optimized according to the spectrum monitoring results, namely: The most recent period of time is used as the statistical period, and the spectrum points of the tracking task frequency are selected from the time-frequency-amplitude statistical information of the spectrum monitoring results. The frequency tolerance is set to the radar frequency measurement accuracy. When the task frequency is , the radar frequency measurement accuracy is , then the frequency of the selected spectrum Need to meet: ; If the maximum amplitude among the selected spectrum points is , then select the amplitude value from -a to The spectrum points are sorted from small to large according to the arrival time, and the arrival time of adjacent spectrum points is subtracted; When the difference in arrival time between adjacent spectrum points is greater than a certain time, it is considered that the next scan of the detection target starts from this spectrum point, so the spectrum points are divided into different clusters; Then, b spectrum points with the largest amplitude are selected from each cluster and the mean arrival time is calculated; Subtract the mean arrival time of each cluster and calculate the mean of the time difference to get the scanning period of the tracking target; Scan cycle Track and retain data rates, and determine retention duration and retention start time, thereby optimizing retention parameters of passive tracking resources; The dwell time must be greater than the search dwell time. The dwell start time of the tracking target for: ； Where n is the minimum value of N that satisfies the following formula: ； is the arrival time of the last spectrum point cluster of the target, represents the current time, p represents the scheduling time slice, and N is the intermediate parameter.

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