Phased array radar distributed power supply management method and system fusing beamforming

Abstract

The application discloses a kind of phased array radar distributed power supply management method and system of fusion beamforming, it is related to phased array radar power supply management technical field, comprising the following steps: acquisition multi-source basic data, construct phased array radar electric-thermal health atlas, and divide dynamic power supply island, with dynamic power supply island as unit, establish beamforming-distributed power supply management joint optimization objective function, obtain fusion beam weight vector and distributed power supply instruction, according to the time sequence synchronization data, issue switch action instruction and execute clock resynchronization measure, then combine the fusion beam weight vector and the distributed power supply instruction, complete the fusion beamforming of phased array radar and pulse power shaping, combine neural network algorithm, output closed-loop feedback index, realize the closed-loop feedback optimization of phased array radar distributed power supply management, solve the problems of large amount of calculation in traditional technology array element level optimization, power supply health and detection value disconnection and power regulation space-time coordination deficiency.

Description

Technical Field

[0001] This invention relates to the field of power supply management technology for phased array radar, and specifically to a distributed power supply management method and system for phased array radar with fused beamforming. Background Technology

[0002] As phased array radars evolve towards large-scale, high-density arrays and multi-mission integration, traditional distributed power supply architectures face technical bottlenecks in the independent operation of beam control and energy management. Existing technologies often employ fixed subarray divisions or power supply strategies based on single electrical parameters such as voltage or current, neglecting the strong coupling between the radio frequency health status of array elements and the value of detection missions. This leads to a mismatch between power allocation and spatial energy requirements, resulting in energy waste and reduced detection accuracy in cluttered environments. Furthermore, the computational complexity of fully connected-level optimization for tens of thousands of phased array elements explodes exponentially, making it difficult to meet real-time requirements. Moreover, the physical characteristics of hardware buses laid out in regions make it impossible to independently control the switching of each phased array element. In addition, traditional systems suffer from transient power consumption fluctuations causing power instability and asynchronous beam shape and power waveform, severely restricting the overall efficiency and operational reliability of the radar. Therefore, developing a distributed power supply management system for phased array radars that can integrate beamforming has become a key technological direction for improving the overall performance of phased array radars.

[0003] Traditional technologies suffer from problems such as a surge in computational load for phased array element-level optimization, a disconnect between power supply health and detection value, a lack of feedback loops, and insufficient spatiotemporal coordination of power regulation. This invention divides the phased array radar into dynamic power supply islands through dual-dimensional clustering of electro-thermal health maps and detection value density. Using these dynamic power supply islands as units, it achieves spatiotemporal joint regulation of fused beamforming and pulse power shaping, realizing joint optimization of beamforming and distributed power supply. Combined with closed-loop feedback technology, it simultaneously improves the energy efficiency, detection performance, and operational stability of distributed power supply management for phased array radar. Summary of the Invention

[0004] The purpose of this invention is to provide a distributed power supply management method and system for phased array radar with fused beamforming, so as to solve the problems mentioned in the background art.

[0005] To solve the above-mentioned technical problems, the technical solution adopted by the present invention is as follows: Firstly, a distributed power supply management method for phased array radar with fused beamforming, comprising the following steps: Step 1: Collect multi-source basic data. The multi-source basic data includes phased array radar array metadata, distributed power supply link data, observation target data, environmental data, and time-series synchronization data, which lays a complete data foundation for the subsequent fusion of beamforming and distributed power supply management for collaborative optimization. Step 2: Utilize distributed power supply link data to calculate the distributed power supply health index of each phased array element. Construct a phased array radar electrical-thermal health map using phased array radar element data. Combine this with time-series synchronization data to achieve unified time-series processing of the phased array radar electrical-thermal health map, thereby accurately obtaining the real-time power supply capability and thermal distribution status of each phased array element of the phased array radar. Step 3: By combining the phased array radar electro-thermal health map, phased array radar data, observation target data and environmental data, the dynamic power supply island is divided, which significantly reduces the complexity of subsequent distributed power supply management. Step 4: Taking the dynamic power supply island as a unit, establish a joint optimization objective function for beamforming and distributed power supply management, introduce constraints, and use the alternating iterative optimization method to solve the fused beam weight vector and distributed power supply command, providing a basis for fused beamforming and pulse power shaping of phased array radar. Step 5: Based on the timing synchronization data, issue switching action commands and execute clock resynchronization measures. Then, combine the fused beam weight vector and distributed power supply commands to complete the fused beamforming and pulse power shaping of the phased array radar, realizing the distributed power supply management process of the phased array radar with fused beamforming. Step Six: Using the observed target data and combined with the neural network algorithm, build a distributed power supply management closed-loop feedback model, output the closed-loop feedback index, set a distributed power supply management closed-loop optimization mechanism, and realize the closed-loop feedback optimization of distributed power supply management through feedback optimization and joint optimization of the objective function, so that the distributed power supply management method of phased array radar with beamforming in this invention can form a continuous adaptive closed-loop feedback optimization capability.

[0006] A further improvement to the technical solution of this invention is that, in step one, the process of collecting multi-source basic data includes: Deploy acquisition equipment to collect multi-source basic data. The acquisition equipment includes a GPS receiver, vector network analyzer, noise figure analyzer, RF power meter, power analyzer, voltage transformer, current transformer, oscilloscope, battery management system built-in acquisition module, temperature sensor and time interval counter. The phased array radar's metadata includes the phased array element position coordinates and the transmission efficiency, phase deviation, and noise figure of the transceiver channels; the distributed power supply link data includes the voltage, voltage ripple, current, peak-to-peak ripple value, and transient voltage drop of each power supply branch, the state of charge of the local energy storage unit, and the temperature and remaining thermal margin of each DC-DC conversion module; the observed target data includes the observed target's distance, reflection intensity, echo fluctuation, and signal-to-noise ratio; the environmental data includes clutter intensity maps and interference intensity maps of the phased array radar environment; and the timing synchronization data includes the clock deviation, clock alignment deviation, and pulse triggering time deviation of the master clock, subarray clock, and power supply controller clock. In this invention, the phased array radar's elements are simply referred to as phased array elements. Data cleaning and normalization are performed on the collected phased array radar array metadata, distributed power supply link data, observed target data, temperature and time synchronization data of the phased array radar environment to eliminate the influence of dimensions in subsequent formula calculations, and noise reduction processing is performed on the clutter intensity map and interference intensity map of the phased array radar environment. Specifically, by combining a GPS receiver, a vector network analyzer, and a noise figure analyzer, the position coordinates of phased array elements, as well as the phase deviation and noise figure of the transceiver channels, are collected. Radio frequency output power and DC input power are collected using an RF power meter and a power analyzer, respectively. The transmission efficiency of the transceiver channels is obtained by calculating the ratio of RF output power to DC input power. Voltage and current of each power supply branch are collected using voltage and current transformers. Voltage ripple, peak-to-peak ripple, and transient voltage drop of each power supply branch are collected using an oscilloscope. The voltage, current, and temperature of local energy storage units are collected using the built-in acquisition module of the battery management system, and their state of charge is estimated based on the ampere-hour integration method. Temperature sensors are used to collect the current temperature of each DC-DC converter module. Referring to the DC-DC converter module datasheet, the junction-to-ambient thermal resistance and the maximum permissible ambient temperature for each DC-DC converter module are obtained. Combining the current temperature and the maximum permissible ambient temperature of each DC-DC converter module, a formula is used to... Calculate the remaining thermal margin for each DC-DC converter module, where, The remaining thermal margin for each DC-DC converter module, and These are the current temperature and maximum permissible ambient temperature for each DC-DC converter module. To reduce the thermal resistance to the environment; After transmitting electromagnetic waves and receiving the echoes, the phased array radar automatically collects the distance, reflection intensity, echo fluctuation, and signal-to-noise ratio of the observed target by the signal processor, and obtains the automatically collected data from the phased array radar display and control console. The phased array radar also collects the clutter intensity map of the phased array radar environment through its built-in radar receiver, high-speed data acquisition card, and signal processor. The phased array radar also collects the interference intensity map of the phased array radar environment using its built-in spectrum analysis module. The reference pulse of the master clock, the output pulse of the subarray clock, and the output pulse of the power supply controller clock are respectively connected to the time interval counter to read the clock deviation of the master clock, the subarray clock, and the power supply controller clock. Using an oscilloscope, the waveforms of the master clock, the subarray clock, and the power supply controller clock are captured respectively. By the time difference between the rising edge and the falling edge of the waveform, the clock alignment deviation and pulse trigger time deviation of the master clock, the subarray clock, and the power supply controller clock are obtained.

[0007] A further improvement to the technical solution of this invention lies in the fact that, in step two, the distributed power supply health index of each phased array element is calculated using distributed power supply link data and phased array radar element data, and the process of constructing a phased array radar electro-thermal health map using phased array radar element data includes: Select the voltage and peak-to-peak ripple of each power supply branch in the distributed power supply link data, as well as the temperature and remaining thermal margin of each DC-DC conversion module; Read the power supply branch design specifications to obtain the rated voltage of each power supply branch. Select the maximum ripple peak value of each power supply branch from the peak-to-peak value of the ripple. Take the maximum ripple peak value of each power supply branch as the upper limit of the peak-to-peak value of the power supply branch. Based on the physical limits of the DC-DC converter module itself and the derating design specifications, set the temperature threshold of the DC-DC converter module. The rated voltage of each power supply branch, the upper limit of the peak-to-peak ripple of the power supply branch, and the temperature threshold of the DC-DC conversion module are normalized to eliminate the influence of subsequent dimensions. Based on the selected data, the distributed power supply health index of each phased array element is calculated. Each element in the phased array radar is numbered, the phased array element number is obtained, and the phased array element number is matched one-to-one with the phased array element position coordinates in the phased array radar data. A two-dimensional coordinate system is established, and the position coordinates of the phased array elements and their corresponding numbers are mapped to the two-dimensional coordinate system to obtain the two-dimensional coordinate system of the phased array physical array surface structure. The number of phased array elements on the horizontal and vertical axes of the two-dimensional coordinate system of the phased array physical array structure is counted to obtain the number of rows and columns of the phased array. Based on the number of rows and columns of the phased array, a two-dimensional matrix is ​​constructed. According to the position coordinates of the phased array elements and their corresponding numbers, the distributed power supply health index of each phased array element is filled into the corresponding position of the two-dimensional matrix to realize the construction of the phased array radar health status matrix. Color coding technology is used to convert the phased array radar health status matrix into a phased array radar electro-thermal health map, providing a spatial constraint basis for the subsequent division of the dynamic power supply island.

[0008] A further improvement to the technical solution of this invention lies in the fact that, in step two, the process of achieving time-series unified processing of the phased array radar's electro-thermal health spectrum through time-series synchronization data includes: Using timing synchronization data, a calculation model of the total time deviation of each phased array element is established through a hierarchical clock deviation modeling algorithm. The total time deviation of each phased array element is obtained, and the total time deviation of each phased array element is mapped to the two-dimensional coordinate system of the phased array physical surface structure to construct a time synchronization error matrix. Based on the time synchronization error matrix and combined with the linear interpolation alignment algorithm, the time-series unified processing of the phased array radar electro-thermal health map is realized to obtain the final phased array radar electro-thermal health map.

[0009] A further improvement to the technical solution of this invention lies in the fact that, in step three, the process of dynamically dividing the power supply island by combining the phased array radar electro-thermal health map, phased array radar data, observed target data, and environmental data includes: Using a two-dimensional clutter statistical estimation technique based on space and time, the clutter intensity of the phased array radar environment is extracted from the clutter intensity map of the phased array radar environment; using a spatial adaptive interference detection and spectrum estimation technique, the interference intensity of the phased array radar environment is extracted from the interference intensity map of the phased array radar environment. The distance and reflection intensity of the observed target in the observation target data and the noise figure of the transceiver channel in the phased array radar array data are selected. According to the transceiver component data manual, the receiver bandwidth is obtained. The clutter intensity and interference intensity of the phased array radar environment and the receiver bandwidth are normalized. The detection value density is calculated by combining the clutter and interference intensity of the phased array radar environment, the distance and reflection intensity of the observed target, the noise figure of the transceiver channel, and the receiver bandwidth. The phased array radar electro-thermal health map is superimposed and fused with the detection value density to calculate the comprehensive score of each phased array element. A dual threshold is set to select phased array elements with a comprehensive score higher than the dual threshold. A clustering algorithm is adopted, based on the principle of spatial proximity and the comprehensive score of each phased array element. Combined with parameters such as the distributed power supply health index and detection value density of each phased array element, clutter intensity and interference intensity of the phased array radar environment, spatial clustering and region merging are performed on array elements with comprehensive scores higher than the dual thresholds. Array elements with adjacent physical locations, similar power supply health status and consistent detection value level are aggregated into independent power supply units, and dynamic power supply islands are adaptively generated to realize the real-time dynamic division of power supply islands that change with the task and environment. Based on the target importance and total power supply capacity of each dynamic power supply island, a unique power supply priority is assigned, and a corresponding independent power supply strategy is matched to realize the division of dynamic power supply islands.

[0010] A further improvement to the technical solution of this invention lies in the following: In step four, taking the dynamic power supply island as a unit, a joint optimization objective function for beamforming and distributed power supply management is established, and constraints are introduced. The process of solving the fused beam weight vector and distributed power supply commands using an alternating iterative optimization method includes: The transmit efficiency and phase deviation of the transceiver channel in the phased array radar data, as well as the voltage, voltage ripple, current and transient voltage drop of each power supply branch in the distributed power supply link data, are selected. Using the selected data, a sensitivity model is established, and the beam gain and phase error penalty terms are calculated. Then, taking the dynamic power supply island as a unit, a joint optimization objective function of beamforming-distributed power supply management is established. Using spatial adaptive interference detection and spectrum estimation technology, the interference intensity map of the phased array radar environment is extracted to obtain the interference source direction angle of the phased array radar environment. By adjusting the interference source direction angle and interference intensity of the phased array radar environment, a beam null is forcibly set. Furthermore, by utilizing the state of charge of the local energy storage unit and the remaining thermal margin of each DC-DC conversion module, the maximum output power of the phased array radar is limited, thereby introducing the constraint condition. Based on the joint optimization objective function of beamforming and distributed power supply management with introduced constraints, an alternating iterative optimization method is used to solve for the fused beam weight vector and distributed power supply command.

[0011] A further improvement to the technical solution of this invention lies in the fact that, in step five, based on the timing synchronization data, a switching action command is issued and a clock resynchronization measure is executed. Combined with the fused beam weight vector and distributed power supply command, the process of completing the fused beamforming and pulse power shaping of the phased array radar includes: A1. Set the pulse trigger time thresholds for the master clock, subarray clock, and power supply controller clock respectively, analyze the pulse trigger time deviations of the master clock, subarray clock, and power supply controller clock, and determine the clock synchronization execution scheme. The clock time synchronization execution scheme includes a switch action issuance scheme and a clock resynchronization scheme. Specifically, when the pulse triggering time deviation of the master clock, subarray clock, and power supply controller clock is within the pulse gap of the phased array radar's transmitted pulse, a switching action command is sent to the phased array radar's distributed power supply network to control the switching array within the power supply array, complete the connection, disconnection, or switching of the power supply branch, realize the physical reconstruction of the distributed power supply path, and establish a channel for subsequent energy injection. This is the switching action sending scheme. When the pulse trigger time deviation of the master clock, subarray clock, or power supply controller clock exceeds its corresponding set threshold, a clock calibration operation is performed to force the clock phase to align and eliminate timing disorder. This is the clock resynchronization scheme. A2. Synchronously inject the fused beam weight vector and distributed power supply command into the phased array radar array system to ensure that the signal modulation actions of the transmitting and receiving signals are highly consistent with the energy output actions of the power supply unit on the time axis. A3. Based on the fusion beam weight vector, adjust the amplitude and phase of the phased array radar's transmitted signal to drive the electromagnetic waves radiated by each array element in the phased array radar, synthesize the desired beam shape in space, and realize fusion beamforming in the distributed power supply management process of the phased array radar. A4. Based on the distributed power supply command, adjust the DC output of each dynamic power supply island, and control the rising edge slope, flat-top ripple and falling edge shape of the pulse to achieve pulse power shaping. The controlled object of fused beamforming is the amplitude ratio and phase difference between each dynamic power supply island, while the controlled object of pulse power shaping is the instantaneous power of a single dynamic power supply island. The combined fused beamforming and pulse power shaping greatly improve the efficiency and accuracy of distributed power supply management for phased array radar.

[0012] A further improvement to the technical solution of this invention lies in the fact that, in step six, the process of building a distributed power supply management closed-loop feedback model and outputting the closed-loop feedback index using observed target data and combined with a neural network algorithm includes: The echo fluctuation and signal-to-noise ratio of the observed target are extracted from the observed target data. The extracted data are integrated into a neural network dataset and divided into a neural network training set and a neural network test set in a 7:3 ratio. Using a neural network algorithm, the neural network training set data is used as input and the closed-loop feedback exponent is used as output. The nonlinear relationship between the echo fluctuation and signal-to-noise ratio of the observed target and the closed-loop feedback exponent is learned to obtain a trained model. The test set data of the neural network is input into the trained model, the model parameters are adjusted, the model performance is optimized, and the final distributed power supply management closed-loop feedback model is obtained. Based on the echo fluctuation and signal-to-noise ratio of the current observed target, the closed-loop feedback index is output.

[0013] A further improvement to the technical solution of this invention lies in the following step: In step six, based on the closed-loop feedback index, a closed-loop optimization mechanism for distributed power supply management is set up to perform feedback optimization on the joint optimization objective function. The process of realizing closed-loop feedback optimization of distributed power supply management for phased array radar with fused beamforming includes: Set a first threshold and a second threshold for closed-loop feedback. Based on the closed-loop feedback index, set a closed-loop optimization mechanism for distributed power supply management and perform feedback optimization on the weight factors of gain, cost and error in the beamforming-distributed power supply management joint optimization objective function. By substituting the weighting factors of gain, cost, and error after feedback optimization into the joint optimization objective function of beamforming-distributed power supply management, the fused beam weight vector and distributed power supply command are re-solved to achieve closed-loop feedback optimization of distributed power supply management for phased array radar with fused beamforming.

[0014] Secondly, a phased array radar distributed power supply management system with fused beamforming is provided to implement the aforementioned phased array radar distributed power supply management method with fused beamforming. The system includes a multi-source data acquisition module, a health map construction module, a dynamic power supply island partitioning module, a joint optimization objective function analysis module, a fused beamforming and pulse power shaping module, and a closed-loop feedback optimization module, wherein each module is communicatively connected. The multi-source data acquisition module collects multi-source basic data, including phased array radar array metadata, distributed power supply link data, observed target data, environmental data, and time-series synchronization data. The health map construction module uses distributed power supply link data to calculate the distributed power supply health index of each phased array element. Through phased array radar element data, it constructs the phased array radar electro-thermal health map and combines it with time-series synchronization data to achieve time-series unified processing of the phased array radar electro-thermal health map. The dynamic power supply island partitioning module combines the phased array radar electro-thermal health map, phased array radar metadata, observation target data and environmental data to realize the dynamic partitioning of power supply islands; The joint optimization objective function analysis module establishes a joint optimization objective function for beamforming and distributed power supply management, taking the dynamic power supply island as a unit. It also introduces constraints and uses an alternating iterative optimization method to solve for the fused beam weight vector and distributed power supply commands. The fusion beamforming and pulse power shaping module, based on timing synchronization data, issues switching action commands and executes clock resynchronization measures. Combined with the fusion beam weight vector and distributed power supply commands, it completes the fusion beamforming and pulse power shaping of the phased array radar. The closed-loop feedback optimization module utilizes observed target data and combines it with neural network algorithms to build a closed-loop feedback model for distributed power supply management, outputs a closed-loop feedback index, and sets up a closed-loop optimization mechanism for distributed power supply management to perform closed-loop feedback optimization on the joint optimization objective function of beamforming-distributed power supply management.

[0015] The beneficial effects of this invention are as follows: Compared with traditional phased array radar distributed power supply management technology, the distributed power supply management method and system of this invention, which integrates multi-source basic data acquisition technology, health map construction technology, dynamic power supply island division technology, distributed power supply management technology of phased array radar with integrated beamforming, and closed-loop feedback technology are closely integrated with modern information technology. Traditional technologies suffer from problems such as a surge in array element-level optimization computation, a disconnect between power supply health and detection value, a lack of feedback closed-loop links, and insufficient spatiotemporal coordination conditions for power regulation. This invention ensures that the method can refine the dynamic monitoring standards for a distributed power supply management method and system of phased array radar with integrated beamforming within a more precise range, making the monitored data more accurate indicators under the same conditions. The development and application of this method significantly enhances the intelligence level in the distributed power supply management process of phased array radar with integrated beamforming. Attached Figure Description

[0016] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments recorded in this invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0017] Figure 1 This is a flowchart of a distributed power supply management method for a phased array radar with integrated beamforming according to the present invention; Figure 2 This is a block diagram of a distributed power supply management system for a phased array radar with integrated beamforming according to the present invention. Figure 3 Electro-thermal health profile of phased array radar; Figure 4 A bar chart showing the relative changes in key performance indicators for distributed power supply closed-loop feedback optimization. Figure 5 A heat map showing the health status of the dynamic power supply island; Figure 6 A three-dimensional scatter plot of the health index of the array element. Detailed Implementation

[0018] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, 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.

[0019] Example 1, such as Figure 1 As shown, this invention provides a distributed power supply management method for phased array radar with fused beamforming, comprising the following steps: S101. Collect multi-source basic data, including phased array radar array metadata, distributed power supply link data, observed target data, environmental data, and time-series synchronization data, which lays the data foundation for the implementation of subsequent steps. S102. Using distributed power supply link data, calculate the distributed power supply health index of each phased array element. Through phased array radar element data, construct the phased array radar electrical-thermal health map. Combined with time-series synchronization data, realize the time-series unified processing of the phased array radar electrical-thermal health map, and provide a basis for the division of dynamic power supply islands. S103. By combining the phased array radar electro-thermal health map, phased array radar data, observation target data and environmental data, dynamic power supply islands are divided, and adjacent array elements in the phased array radar are aggregated into independent dynamic power supply islands, which significantly reduces the complexity of subsequent distributed power supply management. S104. Taking the dynamic power supply island as a unit, a joint optimization objective function of beamforming and distributed power supply management is established, and constraints are introduced. The alternating iterative optimization method is adopted to solve the fused beam weight vector and distributed power supply command, providing technical support for fused beamforming and pulse power shaping of phased array radar. S105. Based on the timing synchronization data, a switch action command is issued and a clock resynchronization measure is executed. Combined with the fused beam weight vector and distributed power supply command, the fused beamforming and pulse power shaping of the phased array radar are completed, realizing the distributed power supply management of the phased array radar with fused beamforming. S106. Using the observed target data and combined with the neural network algorithm, a distributed power supply management closed-loop feedback model is built, the closed-loop feedback index is output, and a distributed power supply management closed-loop optimization mechanism is set. Through feedback optimization and joint optimization of the objective function, the closed-loop feedback optimization of distributed power supply management is realized, so that the distributed power supply management method of phased array radar with beamforming in this invention can form a continuous adaptive closed-loop feedback optimization capability.

[0020] In S101, the process of collecting multi-source basic data includes: Deploy acquisition equipment to collect multi-source basic data. The acquisition equipment includes a GPS receiver, vector network analyzer, noise figure analyzer, RF power meter, power analyzer, voltage transformer, current transformer, oscilloscope, battery management system built-in acquisition module, temperature sensor and time interval counter. The phased array radar's metadata includes the phased array element position coordinates and the transmission efficiency, phase deviation, and noise figure of the transceiver channels; the distributed power supply link data includes the voltage, voltage ripple, current, peak-to-peak ripple value, and transient voltage drop of each power supply branch, the state of charge of the local energy storage unit, and the temperature and remaining thermal margin of each DC-DC conversion module; the observed target data includes the observed target's distance, reflection intensity, echo fluctuation, and signal-to-noise ratio; the environmental data includes clutter intensity maps and interference intensity maps of the phased array radar environment; and the timing synchronization data includes the clock deviation, clock alignment deviation, and pulse triggering time deviation of the master clock, subarray clock, and power supply controller clock. In this invention, the phased array radar's elements are simply referred to as phased array elements. Data cleaning and normalization are performed on the collected phased array radar array metadata, distributed power supply link data, observed target data, temperature and time synchronization data of the phased array radar environment to eliminate the influence of dimensions in subsequent formula calculations, and noise reduction processing is performed on the clutter intensity map and interference intensity map of the phased array radar environment. Specifically, by combining a GPS receiver, a vector network analyzer, and a noise figure analyzer, the position coordinates of the phased array elements, as well as the phase deviation and noise figure of the transceiver channels, are collected. Radio frequency output power and DC input power are collected using an RF power meter and a power analyzer. The transmission efficiency of the transceiver channels is obtained by dividing the RF output power by the DC input power. Voltage and current of each power supply branch are collected using voltage and current transformers. Voltage ripple, peak-to-peak ripple, and transient voltage drop of each power supply branch are collected using an oscilloscope. The voltage, current, and temperature of local energy storage units are collected using the built-in acquisition module of the battery management system, and their state of charge is estimated based on the ampere-hour integration method. Temperature sensors are used to collect the temperature of each DC-DC converter module and its ambient temperature. Referring to the DC-DC converter module datasheet, the junction-to-ambient thermal resistance is obtained. Combined with the temperature of each DC-DC converter module and the maximum permissible ambient temperature, a formula is used to calculate... Calculate the remaining thermal margin for each DC-DC converter module, where, The remaining thermal margin for each DC-DC converter module, and These are the current temperature and maximum permissible ambient temperature for each DC-DC converter module. To reduce the thermal resistance to the environment; After transmitting electromagnetic waves and receiving the echoes, the phased array radar automatically collects the distance, reflection intensity, echo fluctuation, and signal-to-noise ratio of the observed target by the signal processor, and obtains the automatically collected data from the phased array radar display and control console. The phased array radar also collects the clutter intensity map of the phased array radar environment through its built-in radar receiver, high-speed data acquisition card, and signal processor. The phased array radar also collects the interference intensity map of the phased array radar environment using its built-in spectrum analysis module. The reference pulse of the master clock, the output pulse of the subarray clock, and the output pulse of the power supply controller clock are respectively connected to the time interval counter to read the clock deviation of the master clock, the subarray clock, and the power supply controller clock. Using an oscilloscope, the waveforms of the master clock, the subarray clock, and the power supply controller clock are captured respectively. By the time difference between the rising edge and the falling edge of the waveform, the clock alignment deviation and pulse trigger time deviation of the master clock, the subarray clock, and the power supply controller clock are obtained.

[0021] In S102, the distributed power supply health index of each phased array element is calculated using distributed power supply link data and phased array radar element metadata. The process of constructing the phased array radar electro-thermal health map using phased array radar element metadata includes: Select the voltage and peak-to-peak ripple of each power supply branch in the distributed power supply link data, as well as the temperature and remaining thermal margin of each DC-DC conversion module; Read the power supply branch design specifications to obtain the rated voltage of each power supply branch. Select the maximum ripple peak value of each power supply branch from the peak-to-peak value of the ripple. Take the maximum ripple peak value of each power supply branch as the upper limit of the peak-to-peak value of the power supply branch. Based on the physical limits of the DC-DC converter module itself and the derating design specifications, set the temperature threshold of the DC-DC converter module. The rated voltage, peak-to-peak ripple limit, and temperature threshold of the DC-DC converter module for each power supply branch are normalized to eliminate the influence of subsequent dimensions. Based on the selected data, the distributed power supply health index of each phased array element is calculated. The calculation process is as follows: ; in, The distributed power supply health index for each phased array element. The larger the value, the healthier the distributed power supply of the phased array elements; conversely, the smaller the value, the healthier the distributed power supply. The smaller the value, the less healthy the distributed power supply of the phased array elements; , , and These are voltage, ripple, temperature, and remaining thermal margin terms, respectively. Positive terms are positive indicators of the distributed power supply health of the phased array elements, while negative terms are negative indicators of the distributed power supply health of the phased array elements. , , and These are the weights for the voltage term, ripple term, temperature term, and remaining thermal margin term, respectively. and These are the voltage and peak-to-peak ripple values ​​for each power supply branch; and These are the temperature and remaining thermal margin of each DC-DC converter module; , and These are the rated voltage of each power supply branch, the upper limit of the peak-to-peak ripple of the power supply branch, and the temperature threshold of the DC-DC conversion module, respectively. Each element in the phased array radar is numbered, the phased array element number is obtained, and the phased array element number is matched one-to-one with the phased array element position coordinates in the phased array radar data. A two-dimensional coordinate system is established, and the position coordinates of the phased array elements and their corresponding numbers are mapped to the two-dimensional coordinate system to obtain the two-dimensional coordinate system of the phased array physical array surface structure. The number of phased array elements on the horizontal and vertical axes of the two-dimensional coordinate system of the phased array physical array structure is counted to obtain the number of rows and columns of the phased array. Based on the number of rows and columns of the phased array, a two-dimensional matrix is ​​constructed. According to the position coordinates of the phased array elements and their corresponding numbers, the distributed power supply health index of each phased array element is filled into the corresponding position of the two-dimensional matrix to realize the construction of the phased array radar health status matrix. Color coding technology is used to convert the phased array radar health status matrix into a phased array radar electro-thermal health map, providing a spatial constraint basis for the subsequent division of the dynamic power supply island.

[0022] In S102, the process of achieving time-series unified processing of the phased array radar's electro-thermal health map through time-series synchronization data includes: Using timing synchronization data, a calculation model of the total time deviation of each phased array element is established through a hierarchical clock deviation modeling algorithm. The total time deviation of each phased array element is obtained, and the total time deviation of each phased array element is mapped to the two-dimensional coordinate system of the phased array physical surface structure to construct a time synchronization error matrix. Based on the time synchronization error matrix and combined with the linear interpolation alignment algorithm, the time-series unified processing of the phased array radar electro-thermal health map is realized to obtain the final phased array radar electro-thermal health map. Specifically, using timing synchronization data and a hierarchical clock skew modeling algorithm, a calculation model for the total time skew of each phased array element is established. The total time skew of each phased array element is obtained and mapped onto the two-dimensional coordinate system of the phased array physical surface structure, constructing a time synchronization error matrix. This matrix reflects the degree of time asynchrony in different regions of the entire array, providing a correction basis for the subsequent timing unification of the phased array radar electro-thermal health map. The calculation model for the total time skew of each phased array element is as follows: ,in, The total time deviation for each phased array element; , and These are the clock deviation coefficient, clock alignment deviation coefficient, and pulse trigger time deviation coefficient, respectively. , and These are the clock deviations of the master clock, the subarray clock, and the power supply controller clock, respectively. , and These are the clock alignment deviations of the master clock, subarray clock, and power supply controller clock, respectively. , and These are the pulse trigger time deviations of the master clock, subarray clock, and power supply controller clock, respectively. By setting the operating reference time of the phased array radar, and using the time synchronization error matrix and linear interpolation alignment algorithm, the master clock, subarray clock and power supply controller clock are corrected to the time axis corresponding to the operating reference time of the phased array radar, and the final phased array radar electro-thermal health map is obtained.

[0023] In S103, the process of dynamically dividing the power supply island by combining the phased array radar electro-thermal health map, phased array radar metadata, observed target data, and environmental data includes: Using a two-dimensional clutter statistical estimation technique based on space and time, the clutter intensity of the phased array radar environment is extracted from the clutter intensity map of the phased array radar environment; using a spatial adaptive interference detection and spectrum estimation technique, the interference intensity of the phased array radar environment is extracted from the interference intensity map of the phased array radar environment. The distance and reflection intensity of the observed target in the observation target data and the noise figure of the transceiver channel in the phased array radar array data are selected. According to the transceiver component data manual, the receiver bandwidth is obtained. The clutter intensity and interference intensity of the phased array radar environment and the receiver bandwidth are normalized. The detection value density is calculated by combining the clutter and interference intensity of the phased array radar environment, the distance and reflection intensity of the observed target, the noise figure of the transceiver channel, and the receiver bandwidth. The calculation process is as follows: Before calculating the detection value density, it is necessary to first calculate the power required to overcome noise, i.e., the minimum detectable signal power of the phased array radar receiver. A minimum detectable signal-to-noise ratio is set. Based on the phased array radar equations and the receiver sensitivity principle, the formula for calculating the minimum detectable signal power of the phased array radar receiver is as follows: ; ; in, This represents the minimum detectable signal power for a phased array radar receiver. The minimum detectable signal-to-noise ratio. Boltzmann's constant, Standard room temperature, For receiver bandwidth, This represents the noise figure of the transmit / receive channel. For interference power, The interference intensity of the phased array radar environment; The detection value density is calculated based on the power required to overcome noise, and the calculation formula is as follows: ; in, To detect value density; It is a positive proportionality coefficient; To observe the reflection intensity of the target, This is the minimum detectable signal power for a phased array radar receiver; The distance to the observed target; The interference intensity of the phased array radar environment; The clutter intensity of the phased array radar environment; and These are weighting coefficients, used to adjust the weighting of interference and clutter on the detection value. The phased array radar's electro-thermal health map is superimposed and fused with the detection value density to calculate the comprehensive score of each phased array element. A dual threshold is set, and phased array elements with comprehensive scores higher than the dual thresholds are selected. The formula for calculating the comprehensive score of each phased array element is as follows: ; in, Let be the overall score of the i-th phased array element. The distributed power supply health index for each phased array element. To detect value density; here, the subscript i refers to the i-th phased array element; A clustering algorithm is adopted, based on the principle of spatial proximity and the comprehensive score of each phased array element. Combined with parameters such as the distributed power supply health index and detection value density of each phased array element, clutter intensity and interference intensity of the phased array radar environment, spatial clustering and region merging are performed on array elements with comprehensive scores higher than the dual thresholds. Array elements with adjacent physical locations, similar power supply health status and consistent detection value level are aggregated into independent power supply units, and dynamic power supply islands are adaptively generated to realize the real-time dynamic division of power supply islands that change with the task and environment. Based on the target importance and total power supply capacity of each dynamic power supply island, a unique power supply priority is assigned, and a corresponding independent power supply strategy is matched to realize the division of dynamic power supply islands.

[0024] In S104, taking the dynamic power supply island as a unit, a joint optimization objective function of beamforming and distributed power supply management is established, and constraints are introduced. The process of solving the fused beam weight vector and distributed power supply commands using the alternating iterative optimization method includes: The transmit efficiency and phase deviation of the transceiver channel in the phased array radar data, as well as the voltage, voltage ripple, current and transient voltage drop of each power supply branch in the distributed power supply link data, are selected. Using the selected data, a sensitivity model is established, and the beam gain and phase error penalty terms are calculated. Then, taking the dynamic power supply island as a unit, a joint optimization objective function of beamforming-distributed power supply management is established. The derivation of the sensitivity model and the expression for the joint optimization objective function of beamforming-distributed power supply management includes: The formulas for calculating R1 and voltage-gain sensitivity are as follows: ; in, This is the change in gain; This is the voltage-gain sensitivity coefficient; The voltage of each power supply branch; The rated voltage of each power supply branch; The formula for calculating voltage-phase sensitivity is as follows: ; in, This refers to the phase change. This is the DC voltage drop-phase sensitivity coefficient, used for static compensation; Ripple-phase sensitivity coefficient, unit is This describes the instantaneous phase jitter caused by ripple; The voltage of each power supply branch; The rated voltage of each power supply branch; The peak-to-peak value of the ripple for each power supply branch is used to describe the jitter intensity; By fusing and encapsulating the voltage-gain sensitivity coefficient, DC voltage drop-phase sensitivity coefficient, and ripple-phase sensitivity coefficient, a sensitivity model is obtained: ; in, It is the voltage of each power supply branch. The actual launch amplitude below; It is the additional phase shift caused by the voltage and ripple peak-to-peak value of each power supply branch; The reference emission amplitude under rated voltage; The voltage of each power supply branch; The rated voltage of each power supply branch; This is the DC voltage drop-phase sensitivity coefficient, used for static compensation; This is the ripple-phase sensitivity coefficient; For the transmission efficiency of the transceiver channel; This refers to the rated power of the power supply branch; the subscript 'a' here represents the a-th power supply branch. Allocate power to the g-th dynamic power supply island and calculate the voltage based on the allocated power. ,in, Let g be the supply voltage of the g-th dynamic power supply island. The power allocation for the g-th dynamic power supply island, The equivalent resistance of the g-th dynamic power supply island is calculated by combining the voltage transformer and current transformer, along with the equivalent resistance formula. ,in, and All of these measurements were taken by data acquisition equipment; R2 and the formula for calculating beam gain are as follows: ; in, Beam gain; The beam weighting value is the beam weighting value for the g-th dynamic power supply island; This refers to the phase deviation of the transmit and receive channels; For the g-th dynamic power supply island in the target direction The steering vector is derived from the plane wave assumption based on the average position of all array elements in each dynamic power supply island and the desired beam pointing angle. The number of dynamic power supply islands; For the g-th dynamic power supply island, the voltage of its corresponding power supply line is... The actual emission amplitude is obtained from the sensitivity model; The additional phase shift caused by the voltage and ripple peak-to-peak value of the corresponding power supply line of the g-th dynamic power supply island is obtained by the sensitivity model; The formula for calculating the phase error penalty term is as follows: ; in, This is a phase error penalty term; , and These are the power distribution of the g-th dynamic power supply island, the transient voltage drop of each power supply branch in the g-th dynamic power supply island, and the voltage ripple of each power supply branch in the g-th dynamic power supply island, respectively. and These are the DC voltage drop-phase sensitivity coefficient and the ripple-phase sensitivity coefficient, respectively. The number of dynamic power supply islands; The objective function expression for the joint optimization of beamforming and distributed power supply management is as follows: ; in, , and These are the weighting factors for gain, cost, and error, respectively; W is the fused beam weight vector, which determines the amplitude and phase of the transmitted signal of each element in the phased array radar, directly controlling the beam direction and shape; P is the distributed power supply command, i.e., the power allocation vector of each dynamic power supply island, which represents the amount of power allocated to each dynamic power supply island in the phased array radar. , and These are beam gain, power supply cost, and phase error penalty, respectively. The power supply cost is obtained from data entered into the phased array radar power supply system configuration parameter database. Using spatial adaptive interference detection and spectrum estimation techniques, interference intensity maps of the phased array radar environment are extracted to obtain the interference source azimuth angles. By adjusting the interference source azimuth angles and interference intensity, a beam null is forcibly set. Furthermore, by utilizing the state of charge of local energy storage units and the remaining thermal margin of each DC-DC conversion module, the maximum output power of the phased array radar is limited, thus introducing constraints to satisfy... ,in, This represents the maximum output power of the phased array radar. and These represent the state of charge of the local energy storage unit and the remaining thermal margin of each DC-DC conversion module, respectively. Based on the joint optimization objective function of beamforming and distributed power supply management with introduced constraints, an alternating iterative optimization method is used to solve for the fused beam weight vector and distributed power supply command.

[0025] In S105, based on timing synchronization data, switching action commands are issued and clock resynchronization measures are executed. Combined with fused beam weight vectors and distributed power supply commands, the process of fused beamforming and pulse power shaping for the phased array radar includes: A1. Set the pulse trigger time thresholds for the master clock, subarray clock, and power supply controller clock respectively, analyze the pulse trigger time deviations of the master clock, subarray clock, and power supply controller clock, and determine the clock synchronization execution scheme. The clock time synchronization execution scheme includes a switch action issuance scheme and a clock resynchronization scheme. Specifically, when the pulse triggering time deviation of the master clock, subarray clock, and power supply controller clock is within the pulse gap of the phased array radar's transmitted pulse, a switching action command is sent to the phased array radar's distributed power supply network to control the switching array within the power supply array, complete the connection, disconnection, or switching of the power supply branch, realize the physical reconstruction of the distributed power supply path, and establish a channel for subsequent energy injection. This is the switching action sending scheme. When the pulse trigger time deviation of the master clock, subarray clock, or power supply controller clock exceeds its corresponding set threshold, a clock calibration operation is performed to force the clock phase to align and eliminate timing disorder. This is the clock resynchronization scheme. A2. Synchronously inject the fused beam weight vector and distributed power supply command into the phased array radar array system to ensure that the signal modulation actions of the transmitting and receiving signals are highly consistent with the energy output actions of the power supply unit on the time axis. A3. Based on the fusion beam weight vector, adjust the amplitude and phase of the phased array radar's transmitted signal to drive the electromagnetic waves radiated by each array element in the phased array radar, synthesize the desired beam shape in space, and realize fusion beamforming in the distributed power supply management process of the phased array radar. A4. Based on the distributed power supply command, adjust the DC output of each dynamic power supply island, and control the rising edge slope, flat-top ripple and falling edge shape of the pulse to achieve pulse power shaping. The controlled object of fused beamforming is the amplitude ratio and phase difference between each dynamic power supply island, while the controlled object of pulse power shaping is the instantaneous power of a single dynamic power supply island. The combined fused beamforming and pulse power shaping greatly improve the efficiency and accuracy of distributed power supply management for phased array radar.

[0026] In S106, the process of building a distributed power supply management closed-loop feedback model and outputting the closed-loop feedback index using observed target data and neural network algorithms includes: The echo fluctuation and signal-to-noise ratio of the observed target are extracted from the observed target data. The extracted data are integrated into a neural network dataset and divided into a neural network training set and a neural network test set in a 7:3 ratio. Using a neural network algorithm, the neural network training set data is used as input and the closed-loop feedback exponent is used as output. The nonlinear relationship between the echo fluctuation and signal-to-noise ratio of the observed target and the closed-loop feedback exponent is learned to obtain a trained model. The test set data of the neural network is input into the trained model, the model parameters are adjusted, the model performance is optimized, and the final distributed power supply management closed-loop feedback model is obtained. Based on the echo fluctuation and signal-to-noise ratio of the current observed target, the closed-loop feedback index is output.

[0027] In S106, based on the closed-loop feedback index, a closed-loop optimization mechanism for distributed power supply management is set up to perform feedback optimization on the joint optimization objective function. The process of achieving closed-loop feedback optimization of distributed power supply management for phased array radar with fused beamforming includes: Set a first threshold and a second threshold for closed-loop feedback. Based on the closed-loop feedback index, set a closed-loop optimization mechanism for distributed power supply management and perform feedback optimization on the weight factors of gain, cost and error in the beamforming-distributed power supply management joint optimization objective function. Specifically, the first threshold of closed-loop feedback is less than the second threshold of closed-loop feedback. Based on the distributed power supply management requirements of phased array radar, the maximum and minimum values ​​of the gain weight factor, the maximum and minimum values ​​of the cost, the maximum and minimum values ​​of the error, and the adjustment coefficient are set in the beamforming-distributed power supply management joint optimization objective function. When the closed-loop feedback index is less than or equal to the first threshold of closed-loop feedback, the feedback objective of the distributed power supply management of the phased array radar is to prioritize performance. The current gain weight factor is set to the maximum value of the gain weight factor, the current cost weight factor is set to the minimum value of the cost weight factor, and the current error weight factor is set to the minimum value of the error weight factor. This achieves the goal of prioritizing the restoration of core detection capabilities at the expense of economy and purity when performance is severely degraded. When the closed-loop feedback exponent is greater than the first closed-loop feedback threshold and less than the second closed-loop feedback threshold, the feedback objective of the distributed power supply management of the phased array radar is a balanced optimization mode. A continuous linear mapping is used to adjust the weighting factors of gain, cost, and error. The adjustment formula is as follows: ; ; ; in, , and These are the weighting factors for gain, cost, and error before closed-loop feedback, respectively. , and These are the weighting factors for the current gain, cost, and error after closed-loop feedback, respectively. It is a closed-loop feedback index; and These are the set first threshold and second threshold for closed-loop feedback, respectively; , and The adjustment coefficient is set according to the distributed power supply management requirements of phased array radar; When the closed-loop feedback exponent is greater than or equal to the second closed-loop feedback threshold, the feedback objective of the distributed power supply management of the phased array radar prioritizes cost, and the weighting factor of the current gain is reduced to... Adjust the weighting factor of the current cost to [value]. Adjust the weighting factor of the current error to [value]. Once performance targets are met, the focus shifts to optimizing power supply efficiency and signal purity, achieving energy savings and long-life operation. By substituting the weighting factors of gain, cost, and error after feedback optimization into the joint optimization objective function of beamforming-distributed power supply management, the fused beam weight vector and distributed power supply command are re-solved to achieve closed-loop feedback optimization of distributed power supply management for phased array radar with fused beamforming.

[0028] Example 2, as Figure 2 As shown, based on Embodiment 1, the present invention provides a technical solution: a distributed power supply management system for phased array radar with fused beamforming, used to implement the above-mentioned distributed power supply management method for phased array radar with fused beamforming, including a multi-source data acquisition module, a health map construction module, a dynamic power supply island partitioning module, a joint optimization objective function analysis module, a fused beamforming and pulse power shaping module, and a closed-loop feedback optimization module, wherein each module is communicatively connected; The multi-source data acquisition module collects multi-source basic data, including phased array radar array metadata, distributed power supply link data, observed target data, environmental data, and time-series synchronization data. The health map construction module uses distributed power supply link data to calculate the distributed power supply health index of each phased array element. Through phased array radar element data, it constructs the phased array radar electro-thermal health map and combines it with time-series synchronization data to achieve time-series unified processing of the phased array radar electro-thermal health map. The dynamic power supply island partitioning module combines the phased array radar electro-thermal health map, phased array radar metadata, observation target data and environmental data to realize the dynamic partitioning of power supply islands; The joint optimization objective function analysis module establishes a joint optimization objective function for beamforming and distributed power supply management, taking the dynamic power supply island as a unit. It also introduces constraints and uses an alternating iterative optimization method to solve for the fused beam weight vector and distributed power supply commands. The fusion beamforming and pulse power shaping module, based on timing synchronization data, issues switching action commands and executes clock resynchronization measures. Combined with the fusion beam weight vector and distributed power supply commands, it completes the fusion beamforming and pulse power shaping of the phased array radar. The closed-loop feedback optimization module utilizes observed target data and combines it with neural network algorithms to build a closed-loop feedback model for distributed power supply management, outputs a closed-loop feedback index, and sets up a closed-loop optimization mechanism for distributed power supply management to perform feedback optimization on the joint optimization objective function of beamforming and distributed power supply management.

[0029] Example 3, as Figure 3 This is a phased array radar electro-thermal health map. The horizontal axis represents the number of array element columns, and the vertical axis represents the number of array element rows. Each color block represents the distributed power supply health index of an array element. The color bar on the right is a distributed power supply health scale, with a value range of 0 to 1. Red represents high distributed power supply health, and blue represents low distributed power supply health. The closer the color of the block is to dark red, the better the overall electro-thermal performance of the array element, such as power supply voltage stability, ripple suppression, and temperature margin. The closer the color of the block is to dark blue, the more likely the array element has health problems such as power supply fluctuations, high temperature, or insufficient thermal margin. It intuitively presents the health distribution and weak points of the entire phased array.

[0030] Example 4, as Figure 4 A bar chart showing the relative change multiples of key indicators for distributed power supply closed-loop feedback optimization, with the horizontal axis representing the core feedback optimization indicators and the vertical axis representing the relative change multiples. Combination Figure 4 Specifically, the relative change factor of the gain index is 1.10, representing a 10% increase in gain after feedback optimization; the relative change factor of the cost index is 0.97, representing a 3% reduction in power supply cost; and the relative change factor of the error index is 0.96, representing a 4% reduction in phase error. These results directly demonstrate the balanced optimization effect of the closed-loop feedback mechanism in this invention in improving beam performance, controlling power supply cost, and reducing system error.

[0031] Example 5, as Figure 5This is a heatmap of the health status of dynamic power supply islands. The horizontal axis represents the number of array element columns (1~8), and the vertical axis represents the number of array element rows (1~8). The black area represents array elements that were not selected for power supply islands, and the colored area represents healthy array elements that have been assigned to different power supply islands. The color bar on the right is a health scale. The darker the color, the higher the health of the array element. The dark red blocks in the figure are concentrated in multiple connected regions, corresponding to different dynamic power supply islands. This figure intuitively shows the spatial distribution of power supply islands formed by the clustering of array elements with both high health and detection value after screening, as well as the differences in health levels within each power supply island.

[0032] Example 6, as Figure 6 The three-dimensional scatter plot of the array element health index is shown. The X-axis and Y-axis represent the planar position coordinates of the array element in the array (1~8), and the Z-axis represents the distributed power supply health index of the phased array element (0~1). The scatter plot color corresponds to the color bar on the right. Similarly, red indicates high health and blue indicates low health. This figure visually presents the spatial distribution of the array element health index from a three-dimensional perspective: the higher the Z-axis height and the redder the color of the point, the better the overall health status of the array element at that location, providing a spatial dimension visualization basis for the dynamic power supply island division.

[0033] The above description is merely a specific embodiment of this application, but the scope of protection of this application is not limited thereto. Any variations or substitutions that can be easily conceived by those skilled in the art within the scope of the technology disclosed in this application should be included within the scope of protection of this application. Therefore, the scope of protection of this application should be determined by the scope of the claims.

Claims

1. A distributed power supply management method for phased array radar with integrated beamforming, characterized in that, Includes the following steps: Collect multi-source basic data, including phased array radar array metadata, distributed power supply link data, observed target data, environmental data, and time-series synchronization data; Using the distributed power supply link data, the distributed power supply health index of each phased array element is calculated. Through the phased array radar element data, a phased array radar electro-thermal health map is constructed. Combined with the time-series synchronization data, the time-series unified processing of the phased array radar electro-thermal health map is realized. By combining the phased array radar electro-thermal health map, the phased array radar data, the observed target data, and the environmental data, the dynamic division of the power supply island is achieved; Taking the dynamic power supply island as a unit, a joint optimization objective function of beamforming-distributed power supply management is established, and constraints are introduced. The alternating iterative optimization method is used to solve the fused beam weight vector and distributed power supply command. Based on the timing synchronization data, a switching action command is issued and a clock resynchronization measure is executed. Combined with the fused beam weight vector and the distributed power supply command, the fused beamforming and pulse power shaping of the phased array radar are completed. Using the observed target data and combined with neural network algorithms, a closed-loop feedback model for distributed power supply management is built, a closed-loop feedback index is output, a closed-loop optimization mechanism for distributed power supply management is set, and the closed-loop feedback optimization of distributed power supply management is achieved through feedback optimization and joint optimization of the objective function.

2. The distributed power supply management method for phased array radar with fused beamforming according to claim 1, characterized in that, The process of collecting multi-source basic data includes: Deploy acquisition devices to collect the multi-source basic data, wherein the acquisition devices include a GPS receiver, a vector network analyzer, a noise figure analyzer, an RF power meter, a power analyzer, a voltage transformer, a current transformer, an oscilloscope, a battery management system built-in acquisition module, a temperature sensor, and a time interval counter; The phased array radar array metadata includes the phased array element position coordinates and the transmission efficiency, phase deviation, and noise figure of the transceiver channels; the distributed power supply link data includes the voltage, voltage ripple, current, peak-to-peak ripple value, and transient voltage drop of each power supply branch, the state of charge of the local energy storage units, and the temperature and remaining thermal margin of each DC-DC conversion module; the observed target data includes the distance, reflection intensity, echo fluctuation, and signal-to-noise ratio of the observed target; the environmental data includes clutter intensity maps and interference intensity maps of the phased array radar environment; the timing synchronization data includes the clock deviation, clock alignment deviation, and pulse trigger time deviation of the master clock, subarray clock, and power supply controller clock; The collected phased array radar array metadata, distributed power supply link data, observed target data, temperature of the phased array radar environment, and time synchronization data are cleaned and normalized. The clutter intensity map and interference intensity map of the phased array radar environment are denoised.

3. The distributed power supply management method for phased array radar with fused beamforming according to claim 2, characterized in that, The process of calculating the distributed power supply health index of each phased array element using the distributed power supply link data, and constructing the phased array radar electro-thermal health map using the phased array radar data, includes: Select the voltage and peak-to-peak ripple of each power supply branch in the distributed power supply link data, as well as the temperature and remaining thermal margin of each DC-DC conversion module; Read the power supply branch design specifications to obtain the rated voltage of each power supply branch. Select the maximum ripple peak value of each power supply branch from the peak-to-peak ripple values ​​of each power supply branch. Use the maximum ripple peak value of each power supply branch as the upper limit of the peak-to-peak ripple value of the power supply branch. Based on the physical limits of the DC-DC converter module itself and the derating design specifications, set the temperature threshold of the DC-DC converter module. The rated voltage of each power supply branch, the upper limit of the peak-to-peak ripple of the power supply branch, and the temperature threshold of the DC-DC conversion module are normalized. Based on the selected data, the distributed power supply health index of each phased array element is calculated. Each element in the phased array radar is numbered, the phased array element number is obtained, and the phased array element number is matched one-to-one with the phased array element position coordinates in the phased array radar data. A two-dimensional coordinate system is established, and the position coordinates of the phased array elements and their corresponding numbers are mapped to the two-dimensional coordinate system to obtain the two-dimensional coordinate system of the phased array physical array surface structure. The number of phased array elements on the horizontal and vertical axes of the two-dimensional coordinate system of the phased array physical array structure is counted to obtain the number of rows and columns of the phased array. A two-dimensional matrix is ​​constructed by referring to the number of rows and columns of the phased array. Based on the position coordinates of the phased array elements and their corresponding numbers, the distributed power supply health index of each phased array element is filled into the corresponding position of the two-dimensional matrix to realize the construction of the phased array radar health status matrix. Color coding technology is used to convert the phased array radar health status matrix into the phased array radar electro-thermal health map.

4. The distributed power supply management method for phased array radar with fused beamforming according to claim 3, characterized in that, The process of combining the aforementioned time-synchronized data to achieve time-unified processing of the phased array radar's electro-thermal health spectrum includes: Using the aforementioned timing synchronization data, a calculation model for the total time deviation of each phased array element is established through a hierarchical clock deviation modeling algorithm. The total time deviation of each phased array element is obtained, and the total time deviation of each phased array element is mapped to the two-dimensional coordinate system of the phased array physical array surface structure to construct a time synchronization error matrix. Based on the time synchronization error matrix and combined with the linear interpolation alignment algorithm, the time-series unified processing of the phased array radar electro-thermal health map is realized to obtain the final phased array radar electro-thermal health map.

5. The distributed power supply management method for phased array radar with fused beamforming according to claim 4, characterized in that, The process of dynamically dividing the power supply island by combining the phased array radar electro-thermal health map, the phased array radar data, the observed target data, and the environmental data includes: Using a two-dimensional clutter statistical estimation technique based on space and time, the clutter intensity of the phased array radar environment is extracted from the clutter intensity map of the phased array radar environment; using a spatial adaptive interference detection and spectrum estimation technique, the interference intensity of the phased array radar environment is extracted from the interference intensity map of the phased array radar environment. The distance and reflection intensity of the observed target in the observed target data and the noise figure of the transceiver channel in the phased array radar array data are selected. According to the transceiver component data manual, the receiver bandwidth is obtained. The clutter intensity and interference intensity of the phased array radar environment and the receiver bandwidth are normalized. The detection value density is calculated by combining the clutter and interference intensity of the phased array radar environment, the distance and reflection intensity of the observed target, the noise figure of the transceiver channel, and the bandwidth of the receiver. The phased array radar electro-thermal health map is superimposed and fused with the detection value density to calculate the comprehensive score of each phased array element. A dual threshold is set to filter out phased array elements with a comprehensive score higher than the dual threshold. A clustering algorithm is used to merge the selected phased array elements based on the principle of spatial proximity, thereby generating a dynamic power supply island; Based on the target importance and total power supply capacity of each dynamic power supply island, a unique power supply priority is assigned, and a corresponding independent power supply strategy is matched to realize the division of dynamic power supply islands.

6. The distributed power supply management method for phased array radar with fused beamforming according to claim 5, characterized in that, The process of establishing a joint optimization objective function for beamforming and distributed power supply management, using the dynamic power supply island as a unit, introducing constraints, and employing an alternating iterative optimization method to solve for the fused beam weight vector and distributed power supply commands includes: The transmit efficiency and phase deviation of the transceiver channel in the phased array radar array metadata, as well as the voltage, voltage ripple, current and transient voltage drop of each power supply branch in the distributed power supply link data, are selected. Using the selected data, a sensitivity model is established, and beam gain and phase error penalty terms are calculated. Then, taking the dynamic power supply island as a unit, a joint optimization objective function of beamforming-distributed power supply management is established. Using the aforementioned spatial adaptive interference detection and spectrum estimation technology, the interference intensity map of the phased array radar environment is extracted to obtain the interference source direction angle of the phased array radar environment. By adjusting the interference source direction angle and interference intensity of the phased array radar environment, a beam null is forcibly set. Furthermore, by utilizing the state of charge of the local energy storage unit and the remaining thermal margin of each DC-DC conversion module, the maximum output power of the phased array radar is limited, thereby introducing the constraint condition. Based on the joint optimization objective function of beamforming and distributed power supply management with introduced constraints, the fused beam weight vector and the distributed power supply command are solved by the alternating iterative optimization method.

7. The distributed power supply management method for phased array radar with fused beamforming according to claim 6, characterized in that, The process of issuing switching action commands and executing clock resynchronization measures based on the timing synchronization data, and then combining the fused beam weight vector and the distributed power supply command to complete the fused beamforming and pulse power shaping of the phased array radar includes: A1. Set the pulse trigger time thresholds for the master clock, subarray clock, and power supply controller clock respectively, analyze the pulse trigger time deviations of the master clock, subarray clock, and power supply controller clock, and determine the clock synchronization execution scheme. The clock synchronization execution scheme includes a switch action scheme and a clock resynchronization scheme. A2. Synchronously inject the fused beam weight vector and the distributed power supply command into the phased array radar array system; A3. Based on the fused beam weight vector, adjust the amplitude and phase of the phased array radar's transmitted signal to drive the electromagnetic waves radiated by each phased array element in the phased array radar to synthesize the desired beam shape in space, thereby realizing fused beamforming in the distributed power supply management process of the phased array radar. A4. Based on the distributed power supply command, adjust the DC output of each dynamic power supply island and control the rising edge slope, flat-top ripple and falling edge shape of the pulse to achieve pulse power shaping.

8. The distributed power supply management method for phased array radar with fused beamforming according to claim 7, characterized in that, The process of using the observed target data, combined with a neural network algorithm, to build a distributed power supply management closed-loop feedback model and output the closed-loop feedback index includes: The echo fluctuation and signal-to-noise ratio of the observed target are extracted from the observed target data. The extracted data are integrated into a neural network dataset and divided into a neural network training set and a neural network test set. Using the neural network algorithm, the training set data of the neural network is used as input, and the closed-loop feedback index is used as output to learn the nonlinear relationship between the echo fluctuation and signal-to-noise ratio of the observed target and the closed-loop feedback index, so as to obtain a trained model. The test set data of the neural network is input into the trained model, the model parameters are adjusted, the model performance is optimized, and the final distributed power supply management closed-loop feedback model is obtained. Based on the echo fluctuation and signal-to-noise ratio of the observed target, the closed-loop feedback index is output.

9. The distributed power supply management method for phased array radar with fused beamforming according to claim 8, characterized in that, The process of setting up a closed-loop optimization mechanism for distributed power supply management, which achieves closed-loop feedback optimization of distributed power supply management through feedback optimization of the joint optimization objective function, includes: Set a first threshold and a second threshold for closed-loop feedback, and based on the closed-loop feedback index, set the distributed power supply management closed-loop optimization mechanism to perform feedback optimization on the weight factors of gain, cost and error in the beamforming-distributed power supply management joint optimization objective function; Substituting the weighting factors of the feedback-optimized gain, cost, and error into the beamforming-distributed power supply management joint optimization objective function, the fused beam weight vector and distributed power supply command are re-solved to achieve closed-loop feedback optimization of distributed power supply management for phased array radar with fused beamforming.

10. A distributed power supply management system for phased array radar with fused beamforming, used to implement the distributed power supply management method for phased array radar with fused beamforming as described in any one of claims 1-9, comprising a multi-source data acquisition module, a health map construction module, a dynamic power supply island partitioning module, a joint optimization objective function analysis module, a fused beamforming and pulse power shaping module, and a closed-loop feedback optimization module, wherein, The various modules are connected for communication, characterized in that, The multi-source data acquisition module collects multi-source basic data, including phased array radar array metadata, distributed power supply link data, observed target data, environmental data, and time-series synchronization data. The health map construction module uses the distributed power supply link data to calculate the distributed power supply health index of each phased array element, constructs the phased array radar electro-thermal health map through the phased array radar element data, and combines the time-series synchronization data to achieve time-series unified processing of the phased array radar electro-thermal health map. The dynamic power supply island division module, in conjunction with the phased array radar electro-thermal health map, the phased array radar data, the observed target data, and the environmental data, realizes the division of the dynamic power supply island; The joint optimization objective function analysis module establishes a beamforming-distributed power supply management joint optimization objective function using the dynamic power supply island as a unit, introduces constraints, and uses an alternating iterative optimization method to solve for the fused beam weight vector and distributed power supply commands. The fusion beamforming and pulse power shaping module, based on the timing synchronization data, issues a switching action command and executes clock resynchronization measures, and then combines the fusion beam weight vector and the distributed power supply command to complete the fusion beamforming and pulse power shaping of the phased array radar. The closed-loop feedback optimization module utilizes the observed target data and combines it with a neural network algorithm to build a distributed power supply management closed-loop feedback model, outputs a closed-loop feedback index, and sets up a distributed power supply management closed-loop optimization mechanism to perform feedback optimization on the beamforming-distributed power supply management joint optimization objective function, thereby realizing closed-loop feedback optimization of distributed power supply management for phased array radar.

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