A multi-resource adaptive joint scheduling method for ground-based radar facing high-speed targets

Abstract

The application discloses a kind of ground-based radar multi-resource adaptive joint scheduling methods for high-speed target, first in noise and clutter background, ground-based radar system receives and carries out signal processing to the echo in detection airspace, obtains the plot information of detection airspace, then the plot velocity of each wave position is analyzed, then the wave position that appears cross-range cell walk phenomenon calculates the cross-cell walk energy loss coefficient of high-speed target and constructs multi-resource optimization function, finally the adaptive scheduling result of space-time resource and false alarm probability resource is obtained by using CVX toolbox solution, until the overall target detection process is completed.The method of the application considers the energy loss caused by high-speed target range migration, and combines ground-based radar multi-resource cooperative scheduling, realizes the reasonable use of resources while improving the detection performance, the detection performance of high-speed target in clutter and noise environment is significantly improved, and the adaptive optimization of multi-resource cooperative scheduling is realized.

Description

Technical Field

[0001] This invention belongs to the field of ground-based radar technology, specifically relating to a multi-resource adaptive joint scheduling method for ground-based radar targeting high-speed targets. Background Technology

[0002] In complex clutter and noise environments, phased array radar faces severe challenges in detecting moving targets. Existing constant false alarm rate (CFAR) methods rely on a globally uniform false alarm threshold, which cannot adapt to the characteristics of clutter intensity varying with distance and target distribution being non-uniform with angle. This often results in a large number of persistent false alarms remaining in the detection plane, seriously interfering with the identification and tracking of real targets.

[0003] Spacetime resources, primarily including beam pointing, transmission time (i.e., dwell time and pulse count), and transmission power, determine the radar's coverage of the detection airspace and energy allocation. False alarm rate resources refer to the non-uniform false alarm probability configuration based on range cells and wave positions, reflecting the adaptability of the detection threshold to spatial distribution differences. Existing research has analyzed the impact of dwell time on radar detection performance and explored transmission power allocation strategies. Although some works have proposed range-adaptive variable false alarm rate detection methods as alternatives to existing constant false alarm rate methods, current methods still lack joint optimization modeling of spacetime and false alarm rate resources and fail to fully consider the differences in target threat levels along the wave position dimension, thus failing to achieve coordinated scheduling of detection thresholds and transmission resources.

[0004] Therefore, there is an urgent need to develop an advanced detection framework that can improve the target detection performance of radar in complex environments through multi-dimensional joint adaptive optimization of space-time resources and false alarm rate resources. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a ground-based radar multi-resource adaptive joint scheduling method for high-speed targets, which can achieve rational allocation of multiple resources, significantly reduce false alarms in the context of noise and clutter, and realize the rational utilization of resources.

[0006] The technical solution adopted in this invention is: a ground-based radar multi-resource adaptive joint scheduling method for high-speed targets, the specific steps of which are as follows:

[0007] S1. Under the background of noise and clutter, the ground-based radar system receives the echoes in the detection airspace;

[0008] Setting up the first The echo signal received during the second detection The expression is as follows:

[0009] ;

[0010] in, Indicates the amplitude of the received signal. This indicates the radial distance of the current target from the radar base station. This represents the radial velocity of the current target relative to the radar base station. Indicates time delay. Represents the speed of light. Indicates the pulse width. Indicates the center frequency. Indicates the frequency modulation slope. t represents Gaussian white noise, and t represents time.

[0011] S2. Based on step S1, the received echo is processed to obtain the point trace information in the detection space, and then the point trace velocity of each wave position is analyzed.

[0012] First, analyze the echo signal obtained in step S1. Signal processing is performed to obtain the trace information of each wavelet point, and the output trace information is as follows: .

[0013] in, , and They respectively represent the existence of the first Wave position The speed, distance, and angle of each dot.

[0014] Then, the point velocity at each wave position is analyzed, and the maximum value of the point velocity at each wave position is taken. As a reference value, the range cell travel corresponding to each wave position reference value is calculated by setting an upper limit based on the radar transmitted pulse number. And introduce the walking coefficient To determine whether there is cross-range cell movement within this wave position, i.e., whether there is a high-speed target, the movement coefficient expression is as follows:

[0015] ;

[0016] in, Indicates the bandwidth of the radar system. This indicates the maximum dwell time that the radar can allocate to each wave position. Indicates the first No cross-distance cell movement was observed in the wave position. Then it means the first Wave positions exhibit cross-distance cell movement.

[0017] Finally, after the judgment is completed, the result is output.

[0018] S3. Based on step S2, calculate the cross-cell movement energy loss coefficient of the high-speed target for the wave position where cross-cell movement occurs;

[0019] Based on the trace velocity information of each wavelet in the detection space obtained in step S2 Calculate the cross-cell movement energy loss coefficient for each point. To collect all points within each wave position By summing and accumulating the results, the energy loss coefficient for that wavelength can be obtained. .

[0020] S4. Construct a multi-resource optimization function using the cross-unit energy loss coefficients obtained in step S3;

[0021] First, for the multi-resource allocation problem, we construct an optimization function, expressed as follows:

[0022] ;

[0023] in, This indicates the total number of wavelengths in the detected airspace. Indicates the signal-to-noise ratio, and ; Indicates the transmit antenna gain. Indicates the receiving antenna gain. Indicates the radar operating wavelength. Indicates the target's radar cross-section. Represents the clutter backscattering coefficient per unit area. This represents the area of ​​the clutter region illuminated by the radar beam. Indicates the radial distance of the target. Represents the total system loss factor. Represents Boltzmann's constant. Indicates standard noise temperature. Indicates the receiver noise figure. This indicates that the radar base station was assigned to the first... The dwell time of the wave, i.e. , Indicates the number of pulses. Indicates the radar base station's position on the first... Wavelength detection power.

[0024] Furthermore, if the total number of transmitted pulses and the overall transmission power of the radar base station are fixed, then for and The upper and lower limits are constrained, and the constraint condition expression is as follows:

[0025] ;

[0026] in, This indicates the total dwell time of the radar during one scan of the detection airspace. This represents the total transmit power of the radar during a single scan of the detection airspace. This indicates the minimum dwell time that the radar can allocate to each wave position. This indicates the maximum dwell time that the radar can allocate to each wave position. This indicates the minimum transmit power that the radar can allocate to each wave position. This indicates the maximum transmit power that the radar can allocate to each wave position.

[0027] At the same time The upper and lower limits are constrained as follows:

[0028] ;

[0029] in, This represents the lower limit of the cumulative signal-to-clutter-to-noise ratio (SCR) for each wave position during the optimization process. This represents the upper limit of the signal-to-noise ratio accumulation at each position during the optimization process.

[0030] Furthermore, by combining the variable false alarm framework, the false alarm probability of different wave positions is optimized, and a higher false alarm probability is assigned to wave positions with high-speed targets. Then, a false alarm probability setting matrix is ​​proposed. The expression is as follows:

[0031] ;

[0032] in, Indicates the first False alarm probability of wave position Indicates the first False alarm probability at different distances within a wave position. ,and .

[0033] The optimized function expression for resource allocation based on false alarm probability is then obtained as follows:

[0034] ;

[0035] Then, the detection threshold is continuously increased, so that the detection effect of the radar is continuously improved during the frame-by-frame search process. The specific expression is as follows:

[0036] ;

[0037] in, Indicates the next scan. False alarm probability at different distances within a wave position. This represents the change in the false alarm probability between successive scans.

[0038] Finally, the overall architecture for space-time resource scheduling in the detection of moving targets turning into false alarms was constructed, and the rewritten expression of the optimized function is as follows:

[0039] ;

[0040] S5. Use the CVX toolbox to perform convex optimization on the optimization function constructed in step S4 to obtain the adaptive scheduling results of space-time resources and false alarm probability resources.

[0041] The adaptive scheduling results of the space-time resources and false alarm probability resources are the optimized results of the number of transmitted pulses, transmission power, and false alarm probability for each wave position.

[0042] S6. Based on the multi-resource optimization results obtained in step S5, the ground-based radar will search the detection airspace for the next frame, repeating steps S1-S5 until the overall target detection process is completed, thereby realizing the multi-resource adaptive joint scheduling of the ground-based radar.

[0043] The ground-based radar receives echo signals from the detection airspace, performs constant false alarm rate (CFAR) detection on the detection plane obtained by the first frame uniform scan, obtains the detection results, constructs an optimization function through the migration coefficient and cross-cell migration energy loss coefficient, and uses the CVX toolbox to solve the optimization function to obtain the multi-resource allocation results of the ground-based radar for the next scan, and then performs the next frame search scan and receives echo signals.

[0044] The beneficial effects of this invention are as follows: First, under noise and clutter backgrounds, the ground-based radar system receives and processes echoes in the detection airspace to obtain point trace information. Then, the point trace velocity of each wave position is analyzed. Next, for wave positions exhibiting range migration, the energy loss coefficient of high-speed targets across cells is calculated, and a multi-resource optimization function is constructed. Finally, the CVX toolbox is used to solve for the adaptive scheduling results of space-time resources and false alarm probability resources, until the overall target detection process is completed, achieving adaptive joint scheduling of multiple resources by the ground-based radar. This invention considers the energy loss caused by range migration of high-speed targets and, combined with multi-resource collaborative scheduling of the ground-based radar, achieves rational resource utilization while improving detection performance. It significantly improves the detection performance of high-speed targets in clutter and noise environments, realizing adaptive optimization of multi-resource collaborative scheduling. Attached Figure Description

[0045] Figure 1 This is a flowchart of a ground-based radar multi-resource adaptive joint scheduling method for high-speed targets according to the present invention.

[0046] Figure 2 This is a detection planar diagram of the first frame, the third frame, and the sixth frame in an embodiment of the present invention.

[0047] Figure 3 The diagram shows the optimized transmit power results for the first, third, and sixth frames in this embodiment of the invention.

[0048] Figure 4 This is a diagram showing the optimized transmission pulse count for the first, third, and sixth frames in an embodiment of the present invention.

[0049] Figure 5 This is a comparison diagram of the method of the present invention and the existing constant false alarm rate (CFAR) detection plane in an embodiment of the present invention. Detailed Implementation

[0050] The method of the present invention will be further described below with reference to the accompanying drawings and embodiments.

[0051] This embodiment uses the scientific computing software Matlab R2021a to conduct simulation experiments to verify its correctness, such as Figure 1 The flowchart of a ground-based radar multi-resource adaptive joint scheduling method for high-speed targets, as shown in the figure, includes the following specific steps:

[0052] S1. Under the background of noise and clutter, the ground-based radar system receives the echoes in the detection airspace;

[0053] Setting up the first The echo signal received during the second detection The expression is as follows:

[0054] ;

[0055] in, Indicates the amplitude of the received signal. This indicates the radial distance of the current target from the radar base station. This represents the radial velocity of the current target relative to the radar base station. Indicates time delay. Represents the speed of light. Indicates the pulse width. Indicates the center frequency. Indicates the frequency modulation slope. t represents Gaussian white noise, and t represents time.

[0056] In this embodiment, the system parameters used are: the center frequency of the transmitted pulse is 500MHz, the signal bandwidth is 2MHz, and the pulse width is 2ms (corresponding to a frequency modulation slope of ). (Hz / s), the receiver sampling frequency is 10MHz, and the received signal-to-noise ratio is -10dB.

[0057] S2. Based on step S1, the received echo is processed to obtain the point trace information in the detection space, and then the point trace velocity of each wave position is analyzed.

[0058] First, analyze the echo signal obtained in step S1. Signal processing is performed to obtain the trace information of each wavelet point, and the output trace information is as follows: .

[0059] in, , and They respectively represent the existence of the first Wave position The speed, distance, and angle of each dot.

[0060] Then, the point velocity at each wave position is analyzed, and the maximum value of the point velocity at each wave position is taken. As a reference value, the range cell travel corresponding to each wave position reference value is calculated by setting an upper limit based on the radar transmitted pulse number. And introduce the walking coefficient To determine whether there is cross-range cell movement within this wave position, i.e., whether there is a high-speed target, the movement coefficient expression is as follows:

[0061] ;

[0062] in, Indicates the bandwidth of the radar system. This indicates the maximum dwell time that the radar can allocate to each wave position. Indicates the first No cross-distance cell movement was observed in the wave position. Then it means the first Wave positions exhibit cross-distance cell movement.

[0063] Finally, after the judgment is completed, the result is output.

[0064] S3. Based on step S2, calculate the cross-cell movement energy loss coefficient of the high-speed target for the wave position where cross-cell movement occurs;

[0065] Based on the trace velocity information of each wavelet in the detection space obtained in step S2 Calculate the cross-cell movement energy loss coefficient for each point. To collect all points within each wave position By summing and accumulating the results, the energy loss coefficient for that wavelength can be obtained. .

[0066] S4. Construct a multi-resource optimization function using the cross-unit energy loss coefficients obtained in step S3;

[0067] First, for the multi-resource allocation problem, we construct an optimization function, expressed as follows:

[0068] ;

[0069] in, This indicates the total number of wavelengths in the detected airspace. Indicates the signal-to-noise ratio, and ; Indicates the transmit antenna gain. Indicates the receiving antenna gain. Indicates the radar operating wavelength. Indicates the target's radar cross-section. Represents the clutter backscattering coefficient per unit area. This represents the area of ​​the clutter region illuminated by the radar beam. Indicates the radial distance of the target. Represents the total system loss factor. Represents Boltzmann's constant. Indicates standard noise temperature. Indicates the receiver noise figure. This indicates that the radar base station was assigned to the first... The dwell time of the wave, i.e. , Indicates the number of pulses. Indicates the radar base station's position on the first... Wavelength detection power.

[0070] Since the total transmission resources of a radar base station are fixed—that is, the total number of transmitted pulses and the overall transmission power of the radar base station are fixed—in order to avoid missed target detection or waste of resources, [the following measures are taken]. and The upper and lower limits are constrained, and the constraint condition expression is as follows:

[0071] ;

[0072] in, This indicates the total dwell time of the radar during one scan of the detection airspace. This represents the total transmit power of the radar during a single scan of the detection airspace. This indicates the minimum dwell time that the radar can allocate to each wave position. This indicates the maximum dwell time that the radar can allocate to each wave position. This indicates the minimum transmit power that the radar can allocate to each wave position. This indicates the maximum transmit power that the radar can allocate to each wave position.

[0073] At the same time The upper and lower limits are constrained as follows:

[0074] ;

[0075] in, This represents the lower limit of the cumulative signal-to-clutter-to-noise ratio (SCR) for each wave position during the optimization process. This represents the upper limit of the signal-to-noise ratio accumulation at each position during the optimization process.

[0076] In conjunction with the variable false alarm framework, the resources that can be optimized include the false alarm probability (or detection threshold) for different wave positions. The closer to the radar base station, the lower the false alarm probability and the higher the threshold. Meanwhile, high-speed targets are often more threatening to the radar system, therefore, wave positions containing high-speed targets also need to be assigned a higher false alarm probability, i.e., a lower threshold value. To avoid missed target detections, a false alarm probability setting matrix is ​​proposed to allocate a higher false alarm probability to wave positions containing high-speed targets. The expression is as follows:

[0077] ;

[0078] in, Indicates the first False alarm probability of wave position Indicates the first False alarm probability at different distances within a wave position. ,and .

[0079] The optimized function expression for resource allocation based on false alarm probability is then obtained as follows:

[0080] ;

[0081] Then, the detection threshold is continuously increased, so that the detection effect of the radar is continuously improved during the frame-by-frame search process. The specific expression is as follows:

[0082] ;

[0083] in, Indicates the next scan. False alarm probability at different distances within a wave position. This represents the change in the false alarm probability between successive scans.

[0084] Finally, the overall architecture for space-time resource scheduling in the detection of moving targets turning into false alarms was constructed, and the rewritten expression of the optimized function is as follows:

[0085] ;

[0086] S5. Use the CVX toolbox to perform convex optimization on the optimization function constructed in step S4 to obtain the adaptive scheduling results of space-time resources and false alarm probability resources.

[0087] The adaptive scheduling results of the space-time resources and false alarm probability resources are the optimized results of the number of transmitted pulses, transmission power, and false alarm probability for each wave position.

[0088] In this embodiment, the detection planes of the first frame, the third frame, and the sixth frame are as follows: Figure 2 As shown, the transmit power optimization results for the first, third, and sixth frames are as follows: Figure 3 As shown, the optimized transmit pulse count results for the first, third, and sixth frames are as follows: Figure 4 As shown.

[0089] in, Figure 2 (a) To analyze the detection plane of the first frame scan, the cross-cell migration loss coefficient for each wave position is [1,1,1,1,1,1,1,0.8]. Then, the CVX toolbox is used to solve this function to obtain the multi-resource optimization results, such as... Figure 3 (a) and Figure 4 As shown in (a). Figure 2 (b) shows the detection plane result of the third frame scan, with the cross-cell migration loss coefficients for each wavelength being [0,1,1,1,0,1,1,0.8]. After solving using the CVX toolbox, the multi-resource optimization result is shown below. Figure 3 (b) and Figure 4 (b). Figure 2 (c) shows the detection plane result of the sixth frame scan, with the cross-cell migration loss coefficient for each wavelength being [0,0,0,0,0,0,0,0.8]. After solving using the CVX toolbox, the multi-resource optimization result is shown below. Figure 3 (c) and Figure 4 (c) At this point, the real targets existing in the first and eighth wave positions have been revealed.

[0090] Depend on Figure 2 It can be seen that, against a background of noise and clutter, the method of this invention can effectively reduce false alarm points caused by clutter and improve target detection performance. Figure 3 , 4 It can be seen that by allocating space-time resources through the method of the present invention, the effective utilization rate of resources is improved.

[0091] S6. Based on the multi-resource optimization results obtained in step S5, the ground-based radar will search the detection airspace for the next frame, repeating steps S1-S5 until the overall target detection process is completed, thereby realizing the multi-resource adaptive joint scheduling of the ground-based radar.

[0092] The ground-based radar receives echo signals from the detection airspace, performs constant false alarm rate (CFAR) detection on the detection plane obtained by the first frame uniform scan, obtains the detection results, constructs an optimization function through the migration coefficient and cross-cell migration energy loss coefficient, and uses the CVX toolbox to solve the optimization function to obtain the multi-resource allocation results of the ground-based radar for the next scan, and then performs the next frame search scan and receives echo signals.

[0093] To illustrate the effectiveness of the method of the present invention, this embodiment also compares the method of the present invention with the results of existing constant false alarm rate (CFAR) detection planes, such as... Figure 5 As shown, where, Figure 5 (a) shows the detection plane results obtained by using the existing constant false alarm rate (CFAR) detection method. Figure 5 (b) shows the detection plane results obtained by the method of the present invention. As can be seen from the figure, compared with the detection results obtained by the method of the present invention, the existing constant false alarm detection plane still has a large number of clutter false alarm points, which affects the detection performance of the real target.

[0094] Simulation results in this embodiment show that the method of the present invention significantly improves the detection performance of targets with different speeds in clutter and noise environments, effectively realizes adaptive optimization of multi-resource collaborative scheduling, and provides a new technical approach for target detection of phased array radar in complex environments.

[0095] In summary, to address the problem of numerous false alarms (SAFs) interfering with target detection in noisy and cluttered environments, this invention investigates the coupling relationship between target motion characteristics, schedulable resources, and signal-to-clutter ratio (SNR). It considers the SNR gain of high-speed targets moving across range cells due to coherent processing time, and the SNR enhancement effect of transmit power. A multi-resource optimization function is constructed using cross-cell energy loss coefficients. Finally, through adaptive scheduling of spatiotemporal resources and false alarm probability resources, the invention aims to improve resource utilization and reduce the number of SNRs caused by clutter. The workflow of this invention fully aligns with the working mechanism of ground-based radar, facilitating engineering implementation.

[0096] Those skilled in the art will recognize that the embodiments described herein are intended to help the reader understand the principles of the invention, and should be understood that the scope of protection of the invention is not limited to such specific statements and embodiments. Various modifications and variations can be made to the invention by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the invention should be included within the scope of the claims of the invention.

Claims

1. A ground-based radar multi-resource adaptive joint scheduling method for high-speed targets, the specific steps of which are as follows: S1. Under the background of noise and clutter, the ground-based radar system receives the echoes in the detection airspace; Setting up the first The echo signal received during the second detection The expression is as follows: ； in, Indicates the amplitude of the received signal. This indicates the radial distance of the current target from the radar base station. This represents the radial velocity of the current target relative to the radar base station. Indicates time delay. Represents the speed of light. Indicates the pulse width. Indicates the center frequency. Indicates the frequency modulation slope. This represents Gaussian white noise, and t represents time. S2. Based on step S1, the received echo is processed to obtain the point trace information in the detection space, and then the point trace velocity of each wave position is analyzed. First, analyze the echo signal obtained in step S1. Signal processing is performed to obtain the trace information of each wavelet point, and the output trace information is as follows: ; in, , and They respectively represent the existence of the first Wave position The speed, distance, and angle of each point; Then, the point velocity at each wave position is analyzed, and the maximum value of the point velocity at each wave position is taken. As a reference value, the range cell travel corresponding to each wave position reference value is calculated by setting an upper limit based on the radar transmitted pulse number. And introduce the walking coefficient To determine whether there is cross-range cell movement within this wave position, i.e., whether there is a high-speed target, the movement coefficient expression is as follows: ； in, Indicates the bandwidth of the radar system. This indicates the maximum dwell time that the radar can allocate to each wave position. Indicates the first No cross-distance cell movement was observed in the wave position. Then it means the first The wave position exhibits cross-distance cell movement; Finally, after evaluation, the result is output. S3. Based on step S2, calculate the cross-cell movement energy loss coefficient of the high-speed target for the wave position where cross-cell movement occurs; Based on the trace velocity information of each wavelet in the detection space obtained in step S2 Calculate the cross-cell movement energy loss coefficient for each point. To collect all points within each wave position By summing and accumulating the results, the energy loss coefficient for that wavelength can be obtained. ; S4. Construct a multi-resource optimization function using the cross-unit energy loss coefficients obtained in step S3; First, for the multi-resource allocation problem, we construct an optimization function, expressed as follows: ； in, This indicates the total number of wavelengths in the detected airspace. Indicates the signal-to-noise ratio, and ; Indicates the transmit antenna gain. Indicates the receiving antenna gain. Indicates the radar operating wavelength. Indicates the target's radar cross-section. Represents the clutter backscattering coefficient per unit area. This represents the area of ​​the clutter region illuminated by the radar beam. Indicates the radial distance of the target. Represents the total system loss factor. Represents Boltzmann's constant. Indicates standard noise temperature. Indicates the receiver noise figure. This indicates that the radar base station was assigned to the first... The dwell time of the wave, i.e. , Indicates the number of pulses. Indicates the radar base station's position on the first... Wavelength detection power; Furthermore, if the total number of transmitted pulses and the overall transmission power of the radar base station are fixed, then for and The upper and lower limits are constrained, and the constraint condition expression is as follows: ； in, This indicates the total dwell time of the radar during one scan of the detection airspace. This represents the total transmit power of the radar during a single scan of the detection airspace. This indicates the minimum dwell time that the radar can allocate to each wave position. This indicates the maximum dwell time that the radar can allocate to each wave position. This indicates the minimum transmit power that the radar can allocate to each wave position. This indicates the maximum transmit power that the radar can allocate to each wave position. At the same time The upper and lower limits are constrained as follows: ； in, This represents the lower limit of the cumulative signal-to-clutter-to-noise ratio (SCR) for each wave position during the optimization process. This represents the upper limit of the signal-to-clutter-to-noise ratio accumulation at each position during the optimization process; Furthermore, by combining the variable false alarm framework, the false alarm probability of different wave positions is optimized, and a higher false alarm probability is assigned to wave positions with high-speed targets. Then, a false alarm probability setting matrix is ​​proposed. The expression is as follows: ； in, Indicates the first False alarm probability of wave position Indicates the first False alarm probability at different distances within a wave position. ,and ; The optimized function expression for resource allocation based on false alarm probability is then obtained as follows: ； Then, the detection threshold is continuously increased, so that the detection effect of the radar is continuously improved during the frame-by-frame search process. The specific expression is as follows: ； in, Indicates the next scan. False alarm probability at different distances within a wave position. This represents the change in the probability of a false alarm between successive scans; Finally, the overall architecture for space-time resource scheduling in the detection of moving targets turning into false alarms was constructed, and the rewritten expression of the optimized function is as follows: ； S5. Use the CVX toolbox to perform convex optimization on the optimization function constructed in step S4 to obtain the adaptive scheduling results of space-time resources and false alarm probability resources. The adaptive scheduling results of the space-time resources and false alarm probability resources are the optimized results of the number of transmitted pulses, transmission power and false alarm probability for each wave position. S6. Based on the multi-resource optimization results obtained in step S5, the ground-based radar will search the detection airspace for the next frame, repeating steps S1-S5 until the overall target detection process is completed, thereby realizing the multi-resource adaptive joint scheduling of the ground-based radar. The ground-based radar receives echo signals from the detection airspace, performs constant false alarm rate (CFAR) detection on the detection plane obtained by the first frame uniform scan, obtains the detection results, constructs an optimization function through the migration coefficient and cross-cell migration energy loss coefficient, and uses the CVX toolbox to solve the optimization function to obtain the multi-resource allocation results of the ground-based radar for the next scan, and then performs the next frame search scan and receives echo signals.

Images