Passive detection resource parameter dynamic optimization system and method based on spectrum monitoring

Abstract

A passive detection resource parameter dynamic optimization system and method based on spectrum monitoring. A spectrum monitoring resource dwell parameter and a passive detection resource dwell parameter are respectively controlled on the basis of task data, a radar received signal and spectrum monitoring data. When a radio frequency signal is received and processed by means of a passive radar system, dynamic optimization of the passive detection resource dwell parameter is periodically performed on the basis of a spectrum monitoring result and in combination with a spectrum knowledge base. According to the passive detection resource parameter dynamic optimization system and method, a search resource parameter can be customized on the basis of an external environment, thereby increasing the probability of intercepting a target during a search dwell. In addition, when the target intercepted during the search is tracked, a tracking resource parameter is dynamically adapted to a tracking target parameter, thereby improving target tracking stability.

Description

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

[0001] This invention belongs to the field of passive phased array radar resource scheduling, specifically involving a system and method for dynamic optimization of passive detection resource parameters based on spectrum monitoring. Background Technology

[0002] With the increasing complexity and variability of the modern electronic environment, the intelligence level of active radar is gradually improving, and modern scenarios place higher demands on radar reconnaissance. Traditional passive radar, lacking adaptability to real-world environments and employing fixed operating modes and scanning methods, can no longer achieve ideal performance. How to improve the intelligence level of passive radar to adapt to environmental changes and mission requirements has become a research topic of great interest in recent years. Against this backdrop, cognitive radar has emerged, providing a direction for future radar intelligence. Resource scheduling, as the control center of radar, is crucial for improving the overall efficiency of phased array radar by studying closed-loop scheduling algorithms for passive detection resources and fully leveraging the characteristics of passive phased array radar to adapt to environmental changes and mission requirements.

[0003] Most existing research on passive phased array radars focuses on adaptive scheduling algorithms. For example, some existing technologies use integrated priority algorithms to achieve adaptive task scheduling, design evaluation functions for scheduling benefits and costs, and improve the comprehensive scheduling capability of multiple tasks; others analyze prior knowledge of a large number of passive radar tasks to dynamically match tasks with radar system resources, focusing on solving the problem of task congestion; still others accumulate radiation intensity values ​​intercepted from key radiation source targets at different angles to identify the areas where the targets appear, thereby adaptively adjusting the radar sector scan center and sector scan range.

[0004] Closed-loop resource scheduling algorithms for radar systems with cognitive capabilities primarily focus on active radars. These algorithms either improve radar anti-jamming capabilities by adjusting transmitted waveforms to effectively avoid interference spectra, or optimize the performance of mobile target detection and tracking in cluttered environments through radar waveform parameter selection based on environmental perception. For example, some existing technologies, considering the closed-loop operation characteristics of cognitive tracking radars, have studied the optimal tracking waveform design under relevant clutter backgrounds. Others start with the cognitive radar architecture, further optimizing it and elucidating the concept and necessity of parameterization. Still others, starting with radar equations and considering the general scheduling requirements of cognitive radars, determine the structure and specific parameters of the parameterized waveform, establishing a complete parameterized waveform.

[0005] The aforementioned technologies mainly focus on the dynamic optimization of active detection resource parameters. However, existing technologies lack research on dynamic optimization algorithms for passive detection resource parameters. Passive detection resource parameters are fixed, and their search resource parameters cannot be customized according to the environment, resulting in a low probability of target interception during search. Furthermore, when tracking intercepted targets, the tracking resource parameters and tracking target parameters are mismatched, making it easy to lose the target. Summary of the Invention

[0006] To address the aforementioned problems, the present invention aims 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 objective of this invention is as follows:

[0008] A dynamic optimization system for passive detection resource parameters based on spectrum monitoring includes a task scheduling module, a spectrum monitoring module, an RF receiving module, and a beam control module.

[0009] The task scheduling module controls the spectrum monitoring resource dwell parameters and passive detection resource dwell parameters based on task data, radar received signals, and spectrum monitoring data from the spectrum monitoring module, and realizes the passive radar system's reception and processing of radio frequency signals through the beam control module and radio frequency receiving module.

[0010] The spectrum monitoring module processes the radio frequency signal to generate spectrum monitoring results, which are then periodically transmitted to the task scheduling module. Based on the spectrum monitoring results and combined with the spectrum knowledge base, the task scheduling module dynamically optimizes the passive detection resource residency parameters.

[0011] Furthermore, 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 residency parameters based on spectrum monitoring data and the spectrum knowledge base.

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

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

[0015] Based on the received passive search task data, the search area is divided into cells according to 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 radio frequency receiving module. After receiving the radio frequency data, the radio frequency receiving module sends it to the spectrum monitoring module.

[0017] Receive the spectrum monitoring results generated by the spectrum monitoring module, and calculate the cumulative amplitude value of the corresponding cell and the mean of the cumulative amplitude values ​​of all cells based on the azimuth-frequency-amplitude statistics in the spectrum monitoring results of the current scheduling period and the spectrum knowledge base.

[0018] The cells are searched and resided in order of their cumulative amplitude values ​​from largest to smallest. For cells whose cumulative amplitude values ​​are less than or equal to the mean, the cell resides for the initial duration. For cells whose cumulative amplitude values ​​are greater than the mean, the cell resides for n times the initial duration. For cells with a cumulative amplitude value of zero, no search or residency is performed. This completes the optimization of the passive search resource residency parameters.

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

[0020] Where A n Let A be the amplitude at the nth spectral point. min W is the minimum amplitude that radar can detect. n The influence degree of the frequency corresponding to the nth spectral point is obtained by looking up the spectral knowledge base, N. a The number of spectrum points in each cell;

[0021] The average of the summation values ​​of all cell amplitudes is:

[0022] Where, N g S represents the total number of cells. g (m) represents the cumulative amplitude value of the m-th cell.

[0023] Furthermore, the process of optimizing the passive tracking resource residency parameters is as follows:

[0024] Before the task scheduling module receives spectrum monitoring results for a sufficient duration, it tracks and stays at the radar target update cycle data rate, with a fixed dwell time. After the task scheduling module receives spectrum monitoring results for a sufficient duration, it dynamically optimizes the dwell parameters of the passive tracking resources based on the spectrum monitoring results, i.e.:

[0025] Using a recent period as the statistical duration, select the spectrum points of the tracking task frequency from the time-frequency-amplitude statistics of the spectrum monitoring results, and set the frequency tolerance to the radar frequency measurement accuracy.

[0026] When the task frequency is F taskIf the radar frequency measurement accuracy is f, then the frequency F of the selected spectrum is... s Must satisfy: |F s -F task |≤f;

[0027] If the maximum amplitude of the selected spectrum point is A max Then select the amplitude value from A. max -a to A max The spectrum points are sorted by arrival time from smallest to largest, and the arrival times of adjacent spectrum points are subtracted; 'a' is the magnitude of the decrease in amplitude value of the selected spectrum point relative to Amax.

[0028] 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 target will begin from that spectrum point, thus dividing the spectrum points into different clusters;

[0029] Then, select b spectral points with the largest amplitude from each cluster and calculate the mean arrival time;

[0030] The scanning period of the target is obtained by subtracting the mean arrival times of each cluster and then calculating the mean of the time differences.

[0031] Tracking dwell is performed with the scan period τ as the data rate, and the dwell duration and dwell start time are determined, thereby completing the optimization of the dwell parameters of the passive tracking resource.

[0032] Furthermore, the dwell time must be greater than the search dwell time;

[0033] The starting time t1 of the tracking target's stay is: t1 = t0 + n × τ - 2 * p

[0034] Where n is the minimum value of N satisfying the following formula: t0 + N × τ ≥ T0

[0035] t0 is the arrival time of the last spectrum cluster of the target, T0 represents the current time, p represents the scheduling time slice, and N is an intermediate parameter.

[0036] This invention also provides a method for dynamic optimization of passive detection resource parameters based on spectrum monitoring, using the above-mentioned system, comprising the following steps:

[0037] Step 1: The task scheduling module controls the spectrum monitoring resource dwell parameters and passive detection resource dwell parameters based on task data, radar received signals, and spectrum monitoring data from the spectrum monitoring module.

[0038] Step 2: The beam control module and the radio frequency receiving module control the radar detection beam based on the dwell parameters and receive radio frequency signals;

[0039] 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.

[0040] Step 4: Based on the spectrum monitoring results and combined with the spectrum knowledge base, the task scheduling module dynamically optimizes the passive detection resource residency parameters and returns to Step 1.

[0041] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0042] The present invention combines modules such as task scheduling, spectrum monitoring, beam control, and radio frequency reception into a closed-loop scheduling circuit. The task scheduling periodically receives the spectrum monitoring results output by the spectrum monitoring and combines them with a spectrum knowledge base to achieve dynamic optimization of the passive detection resource dwell parameters. The present invention enables passive phased array radar to adapt to the real environment, solves the resource waste problem caused by the fixed scanning method and tracking mode of traditional passive phased array radar, and improves the utilization rate of radar target detection resources.

[0043] The passive detection resource parameter dynamic optimization of the present invention can customize the search resource parameters according to the external environment, thereby increasing the probability of target interception during the search; at the same time, when tracking the intercepted target, the tracking resource parameters and the tracking target parameters are dynamically adapted to improve the target tracking stability.

[0044] The present invention will be further described below with reference to specific embodiments. Attached Figure Description

[0045] Figure 1 is a schematic diagram of the system architecture for dynamic optimization of passive detection resource parameters based on spectrum monitoring according to the present invention.

[0046] Figure 2 is a schematic diagram of the dynamic optimization process of passive search resource parameters according to the present invention.

[0047] Figure 3 is a schematic diagram of the dynamic optimization process of passively tracking resource parameters according to the present invention.

[0048] Figure 4 is a schematic diagram of azimuth-frequency-amplitude monitoring data in an embodiment of the present invention.

[0049] Figure 5 is a schematic diagram of time-frequency-amplitude monitoring data in an embodiment of the present invention. Detailed Implementation

[0050] Example

[0051] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. The described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0052] As indicated in this application and claims, unless the context clearly indicates otherwise, the words "a," "an," "an," and / or "the" do not specifically refer to the singular and may also include the plural. Generally speaking, the terms "comprising" and "including" only indicate the inclusion of explicitly identified steps and elements, which do not constitute an exclusive list, and the method or apparatus may also include other steps or elements.

[0053] Unless otherwise specifically stated, the relative arrangement, numerical expressions, and values ​​of the components and steps described in these embodiments do not limit the scope of this application. It should also be understood that, for ease of description, the dimensions of the various parts shown in the drawings are not drawn to actual scale. Techniques, methods, and devices known to those skilled in the art may not be discussed in detail, but where appropriate, such techniques, methods, and devices should be considered part of the specification. In all examples shown and discussed herein, any specific values ​​should be interpreted as merely exemplary and not as limitations. Therefore, other examples of exemplary embodiments may have different values. It should be noted that similar reference numerals and letters in the following drawings denote similar items; therefore, once an item is defined in one drawing, it need not be further discussed in subsequent drawings.

[0054] Referring to Figure 1, a dynamic optimization system for passive detection resource parameters based on spectrum monitoring includes a task scheduling module, a spectrum monitoring module, a radio frequency receiving module, and a beam control module.

[0055] The task scheduling module periodically receives the spectrum monitoring results output by the spectrum monitoring module, and controls the spectrum monitoring resource dwell parameters and passive detection resource dwell parameters based on the task data, radar received signals and spectrum monitoring data from the spectrum monitoring module, and realizes the passive radar system's reception and processing of radio frequency signals through the beam control module and radio frequency receiving module.

[0056] The spectrum monitoring module processes the radio frequency signal to generate spectrum monitoring results, which are then periodically transmitted to the task scheduling module. Based on the spectrum monitoring results and combined with the spectrum knowledge base, the task scheduling module dynamically optimizes the passive detection resource residency parameters.

[0057] The spectrum monitoring results include statistical information such as azimuth-frequency-amplitude and time-frequency-amplitude of the current passive phased array radar's surrounding environment or radiation source targets.

[0058] The spectrum knowledge base includes: spectrum data stored in terms of impact, represented as impact-frequency values ​​or impact-frequency ranges.

[0059] 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 for spectrum monitoring is 5ms, and the radar target detection scanning cycle ranges from 1s to 10s.

[0060] The passive detection resource residency parameters include passive search resource residency parameters and passive tracking resource residency parameters.

[0061] When the task scheduling module receives a passive search task, it dynamically optimizes the passive search resource residency parameters based on spectrum monitoring data and the spectrum knowledge base.

[0062] When a target to be tracked is found or a passive tracking task is received, the task scheduling module dynamically optimizes the passive tracking resource residency parameters based on spectrum monitoring data and a spectrum knowledge base.

[0063] Specifically, the entire closed-loop workflow is as follows:

[0064] The radar is powered on, and the display shows the control settings for the search scanning area and frequency range. The passive search task is then sent to the task scheduler.

[0065] Task scheduling controls the dwell parameters, such as the start time, dwell frequency, and dwell duration of spectrum monitoring, at 50ms intervals. Each scheduling time slice arranges 10 spectrum monitoring tasks at different frequencies, with a fixed dwell duration of 5ms and a dwell frequency ranging from the start frequency F1 to the end frequency. Circular scan, N f Let t be the total number of frequency points, and assume the start time of the scheduling time slice is t. p Then the start time of each task's stay is: T sp (n)=t p +5*(n-1), 1≤n≤10

[0066] The task scheduler sends the dwell parameters to the beam control, the beam control generates control parameters and sends them to the radio frequency receiver, and the radio frequency receiver sends the received radio frequency data to the spectrum monitoring.

[0067] The spectrum monitoring process processes radio frequency data to generate spectrum monitoring results, which include statistical information such as azimuth-frequency-amplitude and time-frequency-amplitude of the current passive phased array radar surrounding environment or radiation source target, as shown in Figures 4 and 5, and sends them to the task scheduler.

[0068] Before the task scheduler receives the panoramic spectrum monitoring results, that is, before the spectrum monitoring completes the full airspace and full frequency band scan, the search task is kept in the order of frequency points from smallest to largest at 50ms intervals, and the dwell time is fixed at 50ms.

[0069] After receiving the panoramic spectrum monitoring results, the task scheduler dynamically optimizes the passive search resource dwell parameters at 50ms intervals, including the following process, as shown in Figure 2:

[0070] Based on the received passive search task data, the search area is divided into cells according to instantaneous bandwidth and instantaneous azimuth coverage;

[0071] 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 radio frequency receiving module. After receiving the radio frequency data, the radio frequency receiving module sends it to the spectrum monitoring module.

[0072] The system receives spectrum monitoring results generated by the spectrum monitoring module. Based on the azimuth-frequency-amplitude statistics in the spectrum monitoring results of the current scheduling period, and in conjunction with the spectrum knowledge base, it calculates the cumulative amplitude value of the corresponding cell and the mean of the cumulative amplitude values ​​of all cells.

[0073] The cumulative value of the corresponding cell is:

[0074] Where A n Let A be the amplitude at the nth spectral point. min W is the minimum amplitude that radar can detect. n The influence degree of the frequency corresponding to the nth spectral point is obtained by looking up the spectral knowledge base, N. a The number of spectrum points in each cell;

[0075] The average of the summation values ​​of all cell amplitudes is:

[0076] Where, N g S represents the total number of cells. g (m) represents the cumulative amplitude value of the m-th cell.

[0077] The cells are searched and resided in descending order of their cumulative amplitude values. For cells with cumulative amplitude values ​​less than or equal to the mean, the cell resides for the initial 50ms duration. For cells with cumulative amplitude values ​​greater than the mean, the cell resides for n times the initial duration, such as twice the initial duration (100ms). For cells with a cumulative amplitude value of zero, no search or residency is performed. This completes the optimization of the passive search resource residency parameters.

[0078] Referring to Figure 3, the process of optimizing the passive tracking resource residency parameters is as follows:

[0079] Before the task scheduling module receives spectrum monitoring results for a sufficient duration, specifically before receiving spectrum monitoring results for three times the maximum scanning period of the radar target (30 seconds in this example), tracking and dwelling are performed according to the radar target update cycle data rate, with a dwelling duration fixed at 1000ms. After the task scheduling receives spectrum monitoring results for a sufficient duration, i.e., after 30 seconds, the dwelling parameters of the passive tracking resources are dynamically optimized based on the spectrum monitoring results, namely:

[0080] Using a recent time period of 30 seconds as the statistical duration, the spectrum points of the tracking task frequency are selected from the time-frequency-amplitude statistics of the spectrum monitoring results, and the frequency tolerance is set to the radar frequency measurement accuracy.

[0081] The selection of spectrum points is based on the following criteria: when the task frequency is F... task If the radar frequency measurement accuracy is f, then the frequency F of the selected spectrum is... s Must satisfy: |F s -F task |≤f;

[0082] If the maximum amplitude of the selected spectrum point is A max Then select the amplitude value from A. max -10 to A max The spectrum points are sorted by arrival time from smallest to largest, and the arrival times of adjacent spectrum points are subtracted.

[0083] When the difference in arrival time between adjacent spectrum points is greater than a certain time, such as 1 second, it is considered that the next scan of the target will begin from that spectrum point. This method divides the spectrum points into different clusters, as shown in Figure 5, which includes 3 spectrum point clusters.

[0084] Then, select 10 spectral points with the largest amplitude from each cluster and calculate the average arrival time;

[0085] The scanning period of the target is obtained by subtracting the mean arrival times of each cluster and then calculating the mean of the time differences.

[0086] Tracking dwell is performed with the scan period τ as the data rate, and the dwell duration and dwell start time are determined, thereby completing the optimization of the dwell parameters of the passive tracking resource.

[0087] The dwell time must be greater than the search dwell time. In this embodiment, the dwell time of the tracking target is set to 4 times the scheduling time slice, but it can also be modified according to the actual situation.

[0088] The starting time t1 of the tracking target's stay is: t1 = t0 + n × τ - 2 * p

[0089] Where n is the minimum value of N satisfying the following formula: t0 + N × τ ≥ T0

[0090] t0 is the arrival time of the last spectrum cluster of the target, T0 represents the current time of resource scheduling (ms), p represents the scheduling time slice, and N is an intermediate parameter.

[0091] This invention also provides a method for dynamic optimization of passive detection resource parameters based on spectrum monitoring, using the above-mentioned system, comprising the following steps:

[0092] Step 1: The task scheduling module controls the spectrum monitoring resource dwell parameters and passive detection resource dwell parameters based on task data, radar received signals, and spectrum monitoring data from the spectrum monitoring module.

[0093] Step 2: The beam control module and the radio frequency receiving module control the radar detection beam based on the dwell parameters and receive radio frequency signals;

[0094] 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.

[0095] Step 4: Based on the spectrum monitoring results and combined with the spectrum knowledge base, the task scheduling module dynamically optimizes the passive detection resource residency parameters and returns to Step 1.

[0096] Among them, the dynamic optimization of passive detection resource dwell parameters includes the optimization of passive search resource dwell parameters and the optimization of passive tracking resource dwell parameters;

[0097] When the task scheduling module receives a passive search task, it dynamically optimizes the passive search resource residency parameters based on spectrum monitoring data and the spectrum knowledge base.

[0098] When a target to be tracked is found or a passive tracking task is received, the task scheduling module dynamically optimizes the passive tracking resource residency parameters based on spectrum monitoring data and a spectrum knowledge base.

[0099] The optimization of the passive search resource residency parameters specifically includes:

[0100] Based on the received passive search task data, the search area is divided into cells according to instantaneous bandwidth and instantaneous azimuth coverage;

[0101] 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 radio frequency receiving module. After receiving the radio frequency data, the radio frequency receiving module sends it to the spectrum monitoring module.

[0102] The system receives spectrum monitoring results generated by the spectrum monitoring module. Based on the azimuth-frequency-amplitude statistics in the spectrum monitoring results of the current scheduling period, and in conjunction with the spectrum knowledge base, it calculates the cumulative amplitude value of the corresponding cell and the mean of the cumulative amplitude values ​​of all cells.

[0103] The cumulative value of the corresponding cell is:

[0104] Where A n Let A be the amplitude at the nth spectral point. min W is the minimum amplitude that radar can detect. n The influence degree of the frequency corresponding to the nth spectral point is obtained by looking up the spectral knowledge base, N. a The number of spectrum points in each cell;

[0105] The average of the summation values ​​of all cell amplitudes is:

[0106] Where, N g S represents the total number of cells. g (m) represents the cumulative amplitude value of the m-th cell;

[0107] The cells are searched and resided in order of their cumulative amplitude values ​​from largest to smallest. For cells whose cumulative amplitude values ​​are less than or equal to the mean, the cell resides for the initial duration. For cells whose cumulative amplitude values ​​are greater than the mean, the cell resides for n times the initial duration. For cells with a cumulative amplitude value of zero, no search or residency is performed. This completes the optimization of the passive search resource residency parameters.

[0108] The optimization of the passive tracking resource residency parameters specifically involves:

[0109] Before the task scheduling module receives spectrum monitoring results for a sufficient duration, it tracks and stays at the radar target update cycle data rate, with a fixed dwell time. After the task scheduling module receives spectrum monitoring results for a sufficient duration, it dynamically optimizes the dwell parameters of the passive tracking resources based on the spectrum monitoring results, i.e.:

[0110] Using a recent period as the statistical duration, select the spectrum points of the tracking task frequency from the time-frequency-amplitude statistics of the spectrum monitoring results, and set the frequency tolerance to the radar frequency measurement accuracy.

[0111] When the task frequency is F task If the radar frequency measurement accuracy is f, then the frequency F of the selected spectrum is... s Must satisfy: |F s -F task |≤f;

[0112] If the maximum amplitude of the selected spectrum point is Amax Then select the amplitude value from A. max -a to A max The spectrum points are sorted by arrival time from smallest to largest, and the arrival times of adjacent spectrum points are subtracted; 'a' is the magnitude of the decrease in amplitude value of the selected spectrum point relative to Amax.

[0113] 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 target will begin from that spectrum point. This method is used to divide the spectrum points into different clusters.

[0114] Then, select b spectral points with the largest amplitude from each cluster and calculate the mean arrival time;

[0115] The scanning period of the target is obtained by subtracting the mean arrival times of each cluster and then calculating the mean of the time differences.

[0116] Tracking dwell is performed with the scan period τ as the data rate, and the dwell duration and dwell start time are determined, thereby completing the optimization of the dwell parameters of the passive tracking resource;

[0117] The dwell time must be greater than the search dwell time;

[0118] The starting time t1 of the tracking target's stay is: t1 = t0 + n × τ - 2 * p

[0119] Where n is the minimum value of N satisfying the following formula: t0 + N × τ ≥ T0

[0120] t0 is the arrival time of the last spectrum cluster of the target, T0 represents the current time, p represents the scheduling time slice, and N is an intermediate parameter.

[0121] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A dynamic optimization system for passive detection resource parameters based on spectrum monitoring, characterized in that, It includes a task scheduling module, a spectrum monitoring module, an RF receiving module, and a beam control module; The task scheduling module controls the spectrum monitoring resource dwell parameters and passive detection resource dwell parameters based on task data, radar received signals, and spectrum monitoring data from the spectrum monitoring module, and realizes the passive radar system's reception and processing of radio frequency signals through the beam control module and radio frequency receiving module. The spectrum monitoring module processes the radio frequency signal to generate spectrum monitoring results, which are then periodically transmitted to the task scheduling module. Based on the spectrum monitoring results and combined with the spectrum knowledge base, the task scheduling module dynamically optimizes the passive detection resource residency parameters.

2. The passive detection resource parameter dynamic optimization system based on spectrum monitoring according to claim 1, characterized in that, The passive detection resource residency parameters include passive search resource residency parameters and passive tracking resource residency parameters; When the task scheduling module receives a passive search task, it dynamically optimizes the passive search resource residency parameters based on spectrum monitoring data and the spectrum knowledge base. When a target to be tracked is found or a passive tracking task is received, the task scheduling module dynamically optimizes the passive tracking resource residency parameters based on spectrum monitoring data and a spectrum knowledge base.

3. The passive detection resource parameter dynamic optimization system based on spectrum monitoring according to claim 2, characterized in that, The process of optimizing the passive search resource residency parameters is as follows: Based on the received passive search task data, the search area is divided into cells according to 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 radio frequency receiving module. After receiving the radio frequency data, the radio frequency receiving module sends it to the spectrum monitoring module. Receive the spectrum monitoring results generated by the spectrum monitoring module, and calculate the cumulative amplitude value of the corresponding cell and the mean of the cumulative amplitude values ​​of all cells based on the azimuth-frequency-amplitude statistics in the spectrum monitoring results of the current scheduling period and the spectrum knowledge base. The cells are searched and resided in order of their cumulative amplitude values ​​from largest to smallest. For cells whose cumulative amplitude values ​​are less than or equal to the mean, the cell resides for the initial duration. For cells whose cumulative amplitude values ​​are greater than the mean, the cell resides for n times the initial duration. For cells with a cumulative amplitude value of zero, no search or residency is performed. This completes the optimization of the passive search resource residency parameters.

4. The passive detection resource parameter dynamic optimization system based on spectrum monitoring according to claim 3, characterized in that, The cumulative value of the corresponding cell is: Where A n Let A be the amplitude of the nth spectral point. min W is the minimum amplitude that radar can detect. n The influence degree of the frequency corresponding to the nth spectral point is obtained by looking up the spectral knowledge base, N. a The number of spectrum points in each cell; The average of the summation values ​​of all cell amplitudes is: Where, N g S represents the total number of cells. g (m) represents the cumulative amplitude value of the m-th cell.

5. The passive detection resource parameter dynamic optimization system based on spectrum monitoring according to claim 2, characterized in that, The process of optimizing the passive tracking resource residency parameters is as follows: Before the task scheduling module receives spectrum monitoring results for a sufficient duration, it tracks and stays at the radar target update cycle data rate, with a fixed dwell time. After the task scheduling module receives spectrum monitoring results for a sufficient duration, it dynamically optimizes the dwell parameters of the passive tracking resources based on the spectrum monitoring results, i.e.: Using a recent period as the statistical duration, select the spectrum points of the tracking task frequency from the time-frequency-amplitude statistics of the spectrum monitoring results, and set the frequency tolerance to the radar frequency measurement accuracy. When the task frequency is F task If the radar frequency measurement accuracy is f, then the frequency F of the selected spectrum is... s Must satisfy: |F s -F task |≤f; If the maximum amplitude of the selected spectrum point is A max Then select the amplitude value from A. max -a to A max The spectrum points are sorted by arrival time from smallest to largest, and the arrival times of adjacent spectrum points are subtracted; 'a' is the magnitude of the decrease in amplitude value of the selected spectrum point relative to Amax. 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 target will begin from that spectrum point, thus dividing the spectrum points into different clusters; Then, select b spectral points with the largest amplitude from each cluster and calculate the mean arrival time; The scanning period of the target is obtained by subtracting the mean arrival times of each cluster and then calculating the mean of the time differences. Tracking dwell is performed with the scan period τ as the data rate, and the dwell duration and dwell start time are determined, thereby completing the optimization of the dwell parameters of the passive tracking resource.

6. The passive detection resource parameter dynamic optimization system based on spectrum monitoring according to claim 5, characterized in that, The dwell time must be greater than the search dwell time; The starting time t1 of the tracking target's stay is: t1 = t0 + n × τ - 2 * p; Where n is the minimum value of N that satisfies the following formula: t0 + N × τ ≥ T0; t0 is the arrival time of the last spectrum cluster of the target, T0 represents the current time, p represents the scheduling time slice, and N is an intermediate parameter.

7. 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, Includes the following steps: Step 1: The task scheduling module controls the spectrum monitoring resource dwell parameters and passive detection resource dwell parameters based on task data, radar received signals, and spectrum monitoring data from the spectrum monitoring module. Step 2: The beam control module and the radio frequency receiving module control the radar detection beam based on the dwell parameters and receive radio frequency 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: Based on the spectrum monitoring results and combined with the spectrum knowledge base, the task scheduling module dynamically optimizes the passive detection resource residency parameters and returns to Step 1.

8. The method for dynamic optimization of passive detection resource parameters based on spectrum monitoring according to claim 7, characterized in that, The dynamic optimization of passive detection resource residency parameters in step 4 includes optimization of passive search resource residency parameters and optimization of passive tracking resource residency parameters. When the task scheduling module receives a passive search task, it dynamically optimizes the passive search resource residency parameters based on spectrum monitoring data and the spectrum knowledge base. When a target to be tracked is found or a passive tracking task is received, the task scheduling module dynamically optimizes the passive tracking resource residency parameters based on spectrum monitoring data and a spectrum knowledge base.

9. The method for dynamic optimization of passive detection resource parameters based on spectrum monitoring according to claim 8, characterized in that, The optimization of the passive search resource residency parameters specifically includes: Based on the received passive search task data, the search area is divided into cells according to 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 radio frequency receiving module. After receiving the radio frequency data, the radio frequency receiving module sends it to the spectrum monitoring module. The system receives spectrum monitoring results generated by the spectrum monitoring module. Based on the azimuth-frequency-amplitude statistics in the spectrum monitoring results of the current scheduling period, and in conjunction with the spectrum knowledge base, it calculates the cumulative amplitude value of the corresponding cell and the mean of the cumulative amplitude values ​​of all cells. The cumulative value of the corresponding cell is: Where A n Let A be the amplitude of the nth spectral point. min W is the minimum amplitude that radar can detect. n The influence degree of the frequency corresponding to the nth spectral point is obtained by looking up the spectral knowledge base, N. a The number of spectrum points in each cell; The average of the summation values ​​of all cell amplitudes is: Where, N g S represents the total number of cells. g (m) represents the cumulative amplitude value of the m-th cell; The cells are searched and resided in order of their cumulative amplitude values ​​from largest to smallest. For cells whose cumulative amplitude values ​​are less than or equal to the mean, the cell resides for the initial duration. For cells whose cumulative amplitude values ​​are greater than the mean, the cell resides for n times the initial duration. For cells with a cumulative amplitude value of zero, no search or residency is performed. This completes the optimization of the passive search resource residency parameters.

10. The method for dynamic optimization of passive detection resource parameters based on spectrum monitoring according to claim 8, characterized in that, The optimization of the passive tracking resource residency parameters specifically involves: Before the task scheduling module receives spectrum monitoring results for a sufficient duration, it tracks and stays at the radar target update cycle data rate, with a fixed dwell time. After the task scheduling module receives spectrum monitoring results for a sufficient duration, it dynamically optimizes the dwell parameters of the passive tracking resources based on the spectrum monitoring results, i.e.: Using a recent period as the statistical duration, select the spectrum points of the tracking task frequency from the time-frequency-amplitude statistics of the spectrum monitoring results, and set the frequency tolerance to the radar frequency measurement accuracy. When the task frequency is F task If the radar frequency measurement accuracy is f, then the frequency F of the selected spectrum is... s Must satisfy: F s -F task ||≤f; If the maximum amplitude of the selected spectrum point is A max Then select the amplitude value from A. max -a to A max The spectrum points are sorted by arrival time from smallest to largest, and the arrival times of adjacent spectrum points are 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 target will begin from that spectrum point, thus dividing the spectrum points into different clusters; Then, select b spectral points with the largest amplitude from each cluster and calculate the mean arrival time; The scanning period of the target is obtained by subtracting the mean arrival times of each cluster and then calculating the mean of the time differences. Tracking dwell is performed with the scan period τ as the data rate, and the dwell duration and dwell start time are determined, thereby completing the optimization of the dwell parameters of the passive tracking resource; The dwell time must be greater than the search dwell time; The starting time t1 of the tracking target's stay is: t1 = t0 + n × τ - 2 * p; Where n is the minimum value of N that satisfies the following formula: t0 + N × τ ≥ T0; t0 is the arrival time of the last spectrum cluster of the target, T0 represents the current time, p represents the scheduling time slice, and N is an intermediate parameter.

Images