A target direction of arrival estimation method and system based on array radar

Abstract

The present invention relates to the field of radar signal processing technology, and specifically to a target direction of arrival estimation method and system based on array radar, comprising the following steps: setting the frequency and angle of radar beam scanning, adjusting the transmit angle and receive sensitivity of the radar array, covering the target motion area, matching the signal coverage range with the target's preset motion pattern, and obtaining the radar coverage configuration. In the present invention, by finely adjusting the frequency and angle of the radar beam scanning, the transmit and receive sensitivity of the radar array is optimized, and coverage of the target motion area is enhanced. This configuration improves coverage accuracy and enhances adaptability to environmental changes, effectively tracking targets in complex environments, and improving the timeliness and accuracy of signal capture by accurately recording the timestamp and intensity of the reflected signal. Calibration processing ensures accurate interpretation of data, and by adjusting the signal separation threshold to extract key signal components, the accuracy of the direction of arrival estimation is enhanced.

Description

Technical Field

[0001] The present invention relates to the field of radar signal processing technology, and in particular to a target direction of arrival estimation method and system based on array radar. Background Art

[0002] The field of radar signal processing technology involves the acquisition, analysis, interpretation, and utilization of signals. This field focuses on extracting valuable information from the raw signals received by radar systems. Signals are complicated by multipath propagation, noise interference, and signal attenuation. Core technologies include signal filtering, detection, estimation, classification, and tracking. Radar signal processing has a wide range of applications in both civilian and military fields, such as weather forecasting, air traffic control, terrain mapping, and the location and identification of enemy targets. Through advanced algorithms such as fast Fourier transforms (FFTs), Kalman filters, and machine learning techniques, this field continues to push the boundaries of radar technology, improving system performance and the accuracy of signal analysis.

[0003] Target direction of arrival (DOA) estimation is a key technology in radar signal processing. It is used to determine the spatial location of the signal source, that is, the direction of incidence of the signal. This method is particularly important for array signal processing. It uses the time difference or phase difference of the signals received by each sensor in the array to calculate the signal's direction of arrival. DOA estimation is widely used in radar systems, sonar systems, and wireless communications. For example, it is used to optimize signal coverage in mobile communications and to quickly and accurately locate the source of distress signals in search and rescue operations. Effective DOA estimation technology can significantly improve the positioning accuracy and reliability of the system.

[0004] The main challenges faced by existing target direction of arrival estimation methods include multipath propagation, noise interference, and signal attenuation, which often lead to increased signal processing complexity and reduced performance. For example, the signal filtering, detection, and classification steps in traditional methods fail to fully adapt to rapidly changing environmental conditions. In particular, when dealing with high-speed moving targets, conventional signal processing techniques have difficulty adjusting and accurately estimating the target position in real time. This technical limitation results in inaccurate target positioning and reduced tracking efficiency. Existing technologies rely on outdated models for dynamic estimation of the direction of arrival and lack sufficient flexibility to handle small changes in the signal. This can lead to signal loss or incorrect positioning at critical moments in applications such as mobile communications and search and rescue. The lack of an effective signal separation mechanism is another key issue. Existing systems are inefficient in high-noise environments and cannot accurately extract target signals, thus affecting the performance and reliability of the overall system. Summary of the Invention

[0005] The purpose of the present invention is to solve the shortcomings of the prior art and to propose a target direction of arrival estimation method and system based on array radar.

[0006] To achieve the above object, the present invention adopts the following technical solution: a target direction of arrival estimation method based on array radar, comprising the following steps:

[0007] S1: Set the frequency and angle of the radar beam scan, adjust the transmit angle and receive sensitivity of the radar array, cover the target movement area, match the signal coverage range with the target preset movement pattern, and obtain the radar coverage configuration;

[0008] S2: using the radar coverage configuration, directionally exciting the radar beam, capturing the target's reflected signal, recording the signal's timestamp and intensity, calibrating the waveform capture time and the beam emission interval, and obtaining a target reflected signal record;

[0009] S3: Analyzing the target reflection signal record, identifying the signal waveform associated with the target motion, adjusting the signal separation threshold, separating the target signal from the ambient noise, and obtaining key signal waveform features;

[0010] S4: Analyze the key signal waveform characteristics, calculate the signal reflection intensity at different angles, compare the simulated reflection results with the real-time reflection data, and obtain a preliminary direction of arrival estimation result;

[0011] S5: Using the preliminary DOA estimation result, fine-tune the direction of the radar array, optimize the alignment of transmit and receive beams, adjust array parameters, and obtain radar DOA estimation records;

[0012] S6: According to the radar direction of arrival estimation record, parameter adjustment is performed, radar parameters are reconfigured, beam emission angle and receiving sensitivity are adjusted, and a radar target positioning solution is generated.

[0013] As a further solution of the present invention, the radar coverage configuration includes scanning frequency setting, transmission angle adjustment, and receiving sensitivity configuration; the target reflection signal record includes time stamp, signal strength level, and waveform time comparison; the key signal waveform characteristics include signal threshold setting, target signal extraction, and environmental noise identification; the preliminary direction of arrival estimation result includes angle difference measurement, reflection intensity measurement, and simulation data comparison; the radar direction of arrival estimation record includes direction fine-tuning, beam alignment accuracy, and parameter optimization configuration; the radar target positioning solution includes beam angle adjustment, sensitivity level, and radar parameter reset.

[0014] As a further solution of the present invention, the steps of setting the frequency and angle of the radar beam scan, adjusting the transmission angle and receiving sensitivity of the radar array, covering the target motion area, matching the signal coverage range with the preset target motion pattern, and obtaining the radar coverage configuration are specifically as follows:

[0015] S101: Setting the frequency and angle of the radar beam scan, adjusting the scan angle to match the size of the monitoring area, and obtaining radar configuration parameters by adjusting the radar transmission angle and receiving sensitivity to match the target motion characteristics;

[0016] S102: Using the radar configuration parameters, fine-tuning the radar frequency response, analyzing the matching degree between the coverage range and the preset target motion pattern in real time, adjusting the signal processing parameters and optimizing the coverage effect, and generating radar coverage range matching data;

[0017] S103: performing signal detection adjustment based on the radar coverage matching data, analyzing target dynamics within the coverage area, matching signal coverage with target behavior, and obtaining radar coverage configuration.

[0018] As a further solution of the present invention, the steps of utilizing the radar coverage configuration, directionally exciting the radar beam, capturing the target's reflected signal, recording the signal's timestamp and intensity, calibrating the waveform capture time and the beam emission interval, and obtaining the target's reflected signal record are as follows:

[0019] S201: Based on the radar coverage configuration, directionally configure radar beam parameters, including beam width and frequency modulation, optimize beam angle and output power, optimize beam capture efficiency, and generate a beam configuration record;

[0020] S202: Using the beam configuration recording, capturing radar signals reflected from multiple angles, recording the timestamp and strength of each signal, adjusting the sensitivity of the receiving antenna and the gain of the signal amplifier to optimize the quality and reliability of the signal, and obtaining a reflection signal record;

[0021] S203: Calibrate the signal time through the reflected signal record, adjust the filter and noise suppression parameters in the signal processor, match the signal strength and time stamp, and construct the target reflected signal record.

[0022] As a further solution of the present invention, the steps of analyzing the target reflection signal record, identifying the signal waveform associated with the target motion, adjusting the signal separation threshold, separating the target signal from the ambient noise, and obtaining the key signal waveform characteristics are specifically as follows:

[0023] S301: Based on the target reflection signal record, perform frequency and time stamp analysis to select signal waveforms that match the target movement frequency, identify key waveforms associated with target position changes by comparing the amplitude and phase information of the waveforms, and generate a key waveform data set;

[0024] S302: Using the key waveform data set, adjusting the separation threshold of the signal processor, separating the target signal from the ambient noise, and obtaining a purified target signal;

[0025] S303: By using the purified target signal and cross-correlation analysis technology, the delay and intensity changes of the signal in the time series are analyzed to extract the key signal components that determine the direction of arrival, so that the analysis results correspond to the target movement dynamics and obtain the key signal waveform characteristics.

[0026] As a further solution of the present invention, the formula of the cross-correlation analysis technology is as follows:

[0027]

[0028] Where R(τ) is the weighted cross-correlation coefficient, x(t) and y(t) are the signals in the time series, τ is the time delay parameter, N is the length of the time series, w(t) is the weight at time point t, and α is the attenuation factor.

[0029] As a further solution of the present invention, the steps of analyzing the key signal waveform characteristics, calculating the signal reflection intensity at different angles, comparing the simulated reflection results with the real-time reflection data, and obtaining a preliminary direction of arrival estimation result are as follows:

[0030] S401: Based on the key signal waveform characteristics, set the angle range and adjust the simulation parameters, adjust the reference signal strength at each angle, perform simulation calculation of the reflection strength for each angle, adjust the simulator to reflect the actual environmental conditions, and generate a simulated angle reflection record;

[0031] S402: using the simulated angle reflection record to compare with the real-time captured reflection data, including setting comparison parameters, adjusting the time window and data sampling frequency, matching the simulated data with the real-time data, and generating a data comparison analysis record;

[0032] S403: Based on the data comparison and analysis records, adjust key parameters in the signal analysis model, including adjusting the signal reception threshold and filtering parameters, optimize the model's response to differentiated signal strengths, and construct a preliminary direction of arrival estimation result.

[0033] As a further embodiment of the present invention, the steps of using the preliminary direction of arrival estimation result to fine-tune the direction of the radar array, optimize the alignment of the transmit and receive beams, adjust the array parameters, and obtain the radar direction of arrival estimation record are specifically as follows:

[0034] S501: Based on the preliminary direction of arrival estimation result, the direction of the radar array is adjusted. By adjusting the inclination and azimuth of the array, it is determined that the main beam of the array is consistent with the expected direction of the target, and radar direction adjustment data is obtained.

[0035] S502: Using the radar direction adjustment data, adjusting the alignment accuracy of the transmit and receive beams, optimizing the beam coverage of the target by fine-tuning the beam width and the transmit angle, and generating beam alignment optimization data;

[0036] S503: Lock the target position according to the beam alignment optimization data, capture the target signal by continuously adjusting the gain and frequency response of the radar, and continuously monitor and verify the effectiveness of the adjustment to obtain the radar direction of arrival estimation record.

[0037] As a further solution of the present invention, the steps of adjusting parameters, reconfiguring radar parameters, adjusting beam transmission angle and receiving sensitivity, and generating a radar target positioning solution are specifically as follows:

[0038] S601: Extracting key data from the radar direction of arrival estimation record, including the optimal beam transmission angle and power requirement, including evaluating each beam angle data, determining the angle value and power output that need to be adjusted, resetting radar parameters based on the data, and generating a parameter adjustment record;

[0039] S602: Adjusting the physical position and angle of the radar transmitting antenna according to the parameter adjustment record, including fine-tuning the antenna position and electronically adjusting the angle accuracy, and adjusting the transmitting power to a new set value, thereby generating a radar transmitting configuration update record;

[0040] S603: Using the radar transmission configuration update record, resetting receiving radar parameters, including adjusting receiving sensitivity and calibrating filter parameters, optimizing overall reception quality, and generating a radar target positioning solution.

[0041] A target direction of arrival estimation system based on array radar, wherein the target direction of arrival estimation system based on array radar is used to execute the above-mentioned target direction of arrival estimation method based on array radar, and the system comprises:

[0042] The radar array configuration module adjusts the scanning frequency and angle of the radar beam within the target motion area, synchronously adjusts the radar transmit and receive sensitivities, configures the radar coverage, and obtains the configured radar coverage data;

[0043] The target signal acquisition module controls the excitation of the radar beam according to the configured radar coverage data, captures the target reflection signal, records the signal timestamp and intensity, adjusts the waveform capture time and the beam emission interval, and obtains the radar target signal record;

[0044] The signal feature separation module records the radar target signal, analyzes the key waveform in the signal, adjusts the signal separation threshold, and distinguishes the target signal from the environmental noise to obtain key signal feature data;

[0045] The direction of arrival simulation module uses the key signal characteristic data to calculate and simulate the angle and signal strength, calibrates the simulation results with the real-time reflection data and optimizes the estimation accuracy to obtain the direction of arrival simulation results;

[0046] The target positioning optimization module fine-tunes the radar array direction based on the DOA simulation results, adjusts the beam transmission and reception alignment, locks the target position, refines the radar parameter configuration, and obtains the radar's target positioning solution.

[0047] Compared with the prior art, the advantages and positive effects of the present invention are:

[0048] In the present invention, the frequency and angle adjustment of the radar beam scanning are refined to optimize the transmit and receive sensitivity of the radar array. This refined configuration enhances the radar system's coverage of the target's motion area. The matching process with the target's preset motion pattern not only improves the accuracy of radar coverage, but also enhances the system's adaptability to environmental changes, enabling more effective tracking of targets in complex environments. By directionally exciting the radar beam and accurately recording the timestamp and intensity of the reflected signal, the timeliness and accuracy of signal capture are improved. This calibration process of signal recording ensures accurate interpretation of the data and helps to effectively separate the target signal from environmental noise. During the signal analysis process, key signal components are further extracted by adjusting the signal separation threshold to enhance the accuracy of the direction of arrival estimation. The analyzed data is used for simulation and compared with real-time data to not only improve the model's predictive ability, but also optimize the alignment of the transmit and receive beams through real-time adjustment. The continuous adjustment process enhances the radar system's response speed and positioning accuracy. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] Figure 1 It is a schematic diagram of the workflow of the present invention;

[0050] Figure 2 This is a detailed flow chart of S1 of the present invention;

[0051] Figure 3 This is a detailed flow chart of S2 of the present invention;

[0052] Figure 4 This is a detailed flow chart of S3 of the present invention;

[0053] Figure 5 This is a detailed flow chart of S4 of the present invention;

[0054] Figure 6 This is a detailed flow chart of S5 of the present invention;

[0055] Figure 7 This is a detailed flow chart of S6 of the present invention;

[0056] Figure 8It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0058] In the description of the present invention, it should be understood that the terms "length," "width," "up," "down," "front," "back," "left," "right," "vertical," "horizontal," "top," "bottom," "inside," "outside," and the like, indicating positions or relationships, are based on the positions or relationships shown in the accompanying drawings and are intended only to facilitate the description of the present invention and simplify the description. They do not indicate or imply that the devices or elements referred to must have a specific orientation, be constructed, or operate in a specific orientation. Therefore, they should not be construed as limiting the present invention. Furthermore, in the description of the present invention, "plurality" means two or more, unless otherwise expressly and specifically defined.

[0059] Example 1

[0060] See also Figure 1 The present invention provides a technical solution, a target direction of arrival estimation method based on array radar, comprising the following steps:

[0061] S1: Sets the frequency and angle of the radar beam scan, adjusts the transmit angle and receive sensitivity of the radar array, fine-tunes the frequency response to cover the target's motion area, and obtains the radar coverage configuration by matching the monitoring signal coverage area with the target's preset motion pattern.

[0062] S2: Using the radar coverage configuration, directionally excite the radar beam to capture the target's reflected signal, record the signal's timestamp and intensity, and obtain the target's reflected signal record by calibrating the waveform capture time and beam emission interval;

[0063] S3: By analyzing the target reflection signal records, identify the key signal waveform associated with the target motion, separate the target signal from the ambient noise by adjusting the signal separation threshold, extract the key signal components that affect the direction of arrival, and obtain the key signal waveform characteristics;

[0064] S4: Analyze key signal waveform characteristics and use simulation technology to calculate signal reflection strength at different angles. By comparing the simulated reflection results with real-time reflection data, adjust the signal analysis model and obtain preliminary direction of arrival estimation results.

[0065] S5: Using the preliminary DOA estimate, fine-tune the radar array direction, optimize the alignment of the transmit and receive beams, adjust the array parameters, lock on the target position, and obtain radar DOA estimate records.

[0066] S6: Based on the radar direction of arrival estimation record, parameter adjustment is performed to reconfigure the radar parameters. By adjusting the beam transmission angle and receiving sensitivity, a radar target positioning solution is generated.

[0067] Radar coverage configuration includes scanning frequency setting, transmission angle adjustment, and receiving sensitivity configuration. Target reflection signal records include time stamps, signal strength levels, and waveform time comparisons. Key signal waveform features include signal threshold settings, target signal extraction, and environmental noise identification. Preliminary direction of arrival estimation results include angle difference measurement, reflection intensity measurement, and simulation data comparison. Radar direction of arrival estimation records include direction fine-tuning, beam alignment accuracy, and parameter optimization configuration. The radar's target positioning solution includes beam angle adjustment, sensitivity level, and radar parameter reset.

[0068] Specifically, if Figure 2 As shown in the figure, the frequency and angle of the radar beam scan are set, the transmission angle and receiving sensitivity of the radar array are adjusted, the target motion area is covered, and the signal coverage range is matched with the preset target motion pattern. The specific steps for obtaining the radar coverage configuration are as follows:

[0069] S101: Set the frequency and angle of the radar beam scan, adjust the scan angle to match the size of the monitoring area, and adjust the radar transmission angle and receiving sensitivity to match the target motion characteristics. The execution process of obtaining the radar configuration parameters is as follows;

[0070] S101: Set the frequency and angle of the radar beam scan. The radar beam frequency is controlled by the program from 20 MHz to 40 MHz to meet the needs of different monitoring ranges. The scanning angle is adjusted to match the size of the monitoring area. The scanning angle is increased from 30 degrees to 60 degrees. It is dynamically adjusted according to the actual width of the area so that the radar beam can cover a wider area. The radar transmission angle and receiving sensitivity are adjusted to match the target motion characteristics. According to the target speed and direction, the transmission angle is adjusted to align with the target motion trajectory. At the same time, the sensitivity of the receiver is enhanced to improve the accuracy of target detection. The radar configuration parameters are obtained. The parameters include the adjusted frequency f′, scanning angle θ, and sensitivity S. The formula is used:

[0071]

[0072] Where f represents the original frequency, Δf represents the frequency adjustment amount, θ represents the scanning angle, S represents the sensitivity, and k represents the coefficient adjusted according to the environment.

[0073] S102: Using radar configuration parameters, fine-tuning the radar's frequency response, and analyzing the match between the coverage range and the target's preset motion pattern in real time, adjusting signal processing parameters and optimizing coverage, the execution process for generating radar coverage range matching data is as follows;

[0074] S102: Using radar configuration parameters, fine-tune the radar's frequency response to adapt to different monitoring environments. Frequency adjustment follows a gradual process from low to high to ensure signal balance within the coverage area. By analyzing the match between the coverage area and the target's preset motion pattern in real time, adjust the signal processing filter parameters based on the target's speed and acceleration data to optimize signal capture capabilities. Adjust signal processing parameters and optimize coverage effects. Dynamically adjust the gain of the signal booster to ensure signal clarity under different conditions. Generate radar coverage matching data β, which includes signal strength and quality assessment data for each monitoring area, using the formula:

[0075]

[0076] Where a represents the signal processing adjustment coefficient, v represents the target velocity, b represents the gain adjustment coefficient, γ represents the target acceleration, c and d are fixed normalization coefficients, and S represents the signal processing sensitivity.

[0077] S103: Using radar coverage matching data, signal detection and adjustment are performed, target dynamics within the coverage area are analyzed, and signal coverage is matched with target behavior. The execution process for obtaining radar coverage configuration is as follows;

[0078] S103: Adjust signal detection based on radar coverage matching data. Analyze the time-varying characteristics of the signal based on the signal strength in each monitoring area. Adjust the detection threshold based on time series analysis to ensure effective capture of dynamic targets. Analyze target dynamics within the coverage area and classify target behavior patterns using statistical models to adjust coverage and signal processing strategies. Match signal coverage with target behavior. Combine historical and real-time target data to optimize coverage strategies and adjust parameters to enhance signal reliability and accuracy. Obtain radar coverage configuration P using the formula:

[0079]

[0080] Among them, α i Represents the adjustment coefficient at different time points, x i represents the signal intensity at the corresponding time point, ω i represents the weight, and n represents the number of sampling points.

[0081] Specifically, if Figure 3As shown in the figure, the steps for obtaining target reflection signal records by using radar coverage configuration, directionally stimulating the radar beam, capturing the target's reflection signal, recording the signal's timestamp and intensity, and calibrating the waveform capture time and beam emission interval are as follows:

[0082] S201: Based on the radar coverage configuration, the radar beam parameters are directionally configured, including beam width and frequency modulation, and the beam angle and output power are optimized to optimize the beam capture efficiency. The execution process of generating the beam configuration record is as follows;

[0083] S201: Based on the radar coverage configuration, the radar beam parameters are directionally configured. The beam width is adjusted from 5 degrees to 15 degrees through the dynamic control module to adapt to different sizes of monitoring areas. The frequency modulation is adjusted from 1% to 3% of the base frequency to match the interference characteristics of different environments. The beam angle and output power are optimized. The optimal beam angle of the target area is automatically calculated and the output power is adjusted according to the target distance to ensure that the signal strength is still effective for distant targets. The capture efficiency of the beam is optimized. The beam coverage effect is monitored through a real-time feedback mechanism. The parameters are automatically adjusted to achieve the optimal state. The beam configuration record B is generated, including the adjusted width, frequency, angle and power parameters. The formula is used:

[0084]

[0085] Where w represents the beam width, f represents the frequency modulation factor, θ represents the beam angle, P represents the output power, and N represents the environmental noise factor.

[0086] S202: Use beam configuration recording to capture radar signals reflected from multiple angles, record the timestamp and strength of each signal, adjust the sensitivity of the receiving antenna and the gain of the signal amplifier to optimize the quality and reliability of the signal. The execution process for obtaining the reflected signal record is as follows;

[0087] S202: Use beam configuration recording to capture radar signals reflected from multiple angles. First, determine the optimal capture angle of the reflected signal, from C degrees to 360 degrees with no blind spot coverage. Record the timestamp and strength of each signal. Each signal acquisition point is marked with a timestamp and signal strength level accurate to milliseconds. Adjust the sensitivity of the receiving antenna from the basic sensitivity to 150% of the maximum sensitivity to ensure the capture of weak signals. Adjust the gain of the signal amplifier, automatically adjusting the gain according to the signal strength to optimize the quality and reliability of the signal. Obtain the reflected signal record R, which includes the signal angle, timestamp, strength, and adjustment parameters. The formula is used:

[0088]

[0089] Among them, s i represents the strength of the i-th signal, ti represents the timestamp of the signal, k represents the time adjustment factor, and G represents the total gain.

[0090] S203: Using the reflected signal record, calibrate the signal time, adjust the filter and noise suppression parameters in the signal processor, match the signal strength and timestamp, and construct the target reflected signal record. The execution process is as follows:

[0091] S203: Calibrate the signal time by recording the reflected signal, fine-tune the timestamp of each signal to ensure the consistency and accuracy of the time, adjust the filter and noise suppression parameters in the signal processor, adjust the filter parameters by analyzing the frequency distribution of the signal, and enhance the noise suppression function to eliminate the influence of environmental noise. Match the signal strength and timestamp, and use a complex algorithm to ensure the accurate correspondence between the timestamp and the signal strength. Construct the target reflected signal record M, which includes the detailed time and strength information of each signal, as well as the adjusted filter and noise suppression settings, using the formula:

[0092]

[0093] Among them, λ i Represents the signal strength adjustment coefficient, v i represents the adjusted signal strength, μ i represents the weight coefficient of the timestamp, and n represents the number of signals.

[0094] Specifically, if Figure 4 As shown in the figure, by analyzing the target reflection signal record, identifying the signal waveform associated with the target motion, adjusting the signal separation threshold, separating the target signal from the ambient noise, and obtaining the key signal waveform characteristics, the specific steps are as follows:

[0095] S301: Based on the target reflection signal records, frequency and timestamp analysis is performed to select signal waveforms that match the target motion frequency. By comparing the amplitude and phase information of the waveforms, key waveforms associated with the target position change are identified. The execution process for generating a key waveform dataset is as follows;

[0096] S301: Based on the target reflection signal record, frequency and time stamp analysis is performed. First, the recorded signal is subjected to a fast Fourier transform (FFT) to separate different frequency components and filter out the components that are consistent with the target motion frequency f. t By comparing the amplitude A and phase φ information of the waveform, the phase difference and amplitude ratio are used for precise matching to identify the key waveforms associated with the target position change and generate a key waveform data set, which includes the frequency, amplitude and phase information of all key waveforms.

[0097] The improved formula is:

[0098]

[0099] Among them, K represents the comprehensive index of the key waveform data set, A i represents the amplitude of the i-th waveform, φ i Represents the phase φ of the i-th waveform t represents the phase of the target waveform, n represents the number of filtered waveforms, and j is an imaginary unit representing the phase operation.

[0100] S302: Using the key waveform data set, adjusting the separation threshold of the signal processor to separate the target signal from the ambient noise, and obtaining the purified target signal. The execution process is as follows;

[0101] S302: Using the key waveform data set, adjust the separation threshold θ in the signal processor. Set it to dynamic adjustment mode and automatically adjust the threshold according to the ambient noise level to maximize the distinction between the signal and noise. Separate the target signal from the ambient noise. Use a high-pass filter and waveform recognition algorithm to extract and purify the target signal from the complex background. Obtain the purified target signal and record parameters including signal clarity and recognition success rate. Use the formula:

[0102] Where P represents the quality index of the purified target signal, s i represents the strength of the i-th signal, θ i Represents the dynamically adjusted separation threshold δ i represents the background noise level of the signal, and n represents the number of signals.

[0103] S303: By purifying the target signal and using cross-correlation analysis technology, the delay and intensity changes of the signal in the time series are analyzed to extract the key signal components that determine the direction of arrival. The analysis results are aligned with the target motion dynamics to obtain the key signal waveform characteristics. The execution process is as follows;

[0104] S303: By purifying the target signal, using cross-correlation analysis technology, the relationship between signals at different time points in the signal sequence is calculated, thereby analyzing the delay τ and intensity changes of the signal in the time series, extracting the key signal components that determine the direction of arrival, and using statistical models and signal processing algorithms to extract key features. The analysis results are aligned with the target motion dynamics, and the key signal waveform features are obtained, including the time delay and amplitude change of the waveform. The formula is:

[0105]

[0106] Where D represents the comprehensive measure of key signal waveform characteristics, x i represents the intensity of the i-th signal component, τ i represents the time delay of the signal, λ irepresents the weight of the signal component, and n represents the number of signal components.

[0107] The formula for the cross-correlation analysis technique is as follows:

[0108]

[0109] Where R(τ) is the weighted cross-correlation coefficient, x(t) and y(t) are the signals in the time series, τ is the time delay parameter, N is the length of the time series, w(t) is the weight at time point t, and α is the attenuation factor.

[0110] The execution process is as follows:

[0111] Calculate the weight w(t) at each time point t, which can be determined by analyzing the signal change intensity in the historical data. Apply the weight w(t) to the product of the original signals x(t) and y(t+τ). Introduce the attenuation factor α, which is used to reduce the impact of signals with large time gaps on the correlation. By summing and standardizing the weighted signal products of all time points, calculate the weighted mutual correlation coefficient R(τ). The exact value of the weight w(t) is determined by an optimization algorithm. The gradient descent method can be used to minimize the prediction error to find the optimal weight configuration.

[0112] Specifically, if Figure 5 As shown in the figure, the steps for analyzing key signal waveform characteristics, calculating the signal reflection intensity at different angles, comparing the simulated reflection results with the real-time reflection data, and obtaining the preliminary direction of arrival estimation result are as follows:

[0113] S401: Based on the key signal waveform characteristics, set the angle range and adjust the simulation parameters, adjust the reference signal strength at each angle, perform a simulation calculation of the reflection intensity for each angle, adjust the simulator to reflect the actual environmental conditions, and generate the simulated angle reflection record. The execution process is as follows;

[0114] S401: Based on the key signal waveform characteristics, set the angle range and adjust the simulation parameters. Set the angle range from 0 degrees to 360 degrees, and simulate with every 5 degrees as an initial angle point. Adjust the baseline signal strength at each angle. According to the pre-analyzed signal characteristics, set the baseline strength corresponding to each angle to simulate the signal reflection strength at different angles. Perform simulation calculations on the reflection strength for each angle, use the adjusted simulation parameters to reflect the signal changes at different angles, calculate through a high-precision physical model, adjust the simulator and reflect the actual environmental conditions, ensure that the simulation results match the signal response in the actual environment, and generate a simulated angle reflection record. The record contains the simulated reflection strength and parameter settings for each angle, using the formula:

[0115]

[0116] Among them, R θ represents the simulated angle reflection record, I θ represents the reference signal strength, θ represents the angle, θ0 represents the target angle, α represents the attenuation coefficient, and N represents the total number of angles.

[0117] S402: Using simulated angle reflection records, comparing them with real-time captured reflection data, including setting comparison parameters, adjusting the time window and data sampling frequency, matching simulated data with real-time data, and generating data comparison analysis records. The execution process is as follows;

[0118] S402: Use simulated angle reflection records to compare with real-time captured reflection data. First, set the comparison parameters, including the amplitude and frequency characteristics of the signal, adjust the time window and data sampling frequency, set the time window to data sampling once every 10 seconds, and the frequency to 500 times per second to ensure the time sensitivity and frequency resolution of the data; match the simulated data with the real-time data, use an advanced data matching algorithm to compare the simulated data set with the actual captured data set to ensure consistency between the two, and generate a data comparison analysis record. The record details the successfully matched data points and their corresponding statistical analysis results, using the formula:

[0119]

[0120] Among them, C represents the difference metric of data comparison, M i represents a simulated data point, R i represents the actual data points, and n represents the total number of data points.

[0121] S403: Based on the data comparison and analysis records, adjust the key parameters in the signal analysis model, including adjusting the signal reception threshold and filtering parameters, optimize the model's response to differentiated signal strengths, and construct a preliminary direction of arrival estimation result. The execution process is as follows;

[0122] S403: Based on the data comparison and analysis records, adjust the key parameters in the signal analysis model and fine-tune the parameters according to the differences in the analysis records. This includes adjusting the signal reception threshold to adapt to changes in different signal strengths, adjusting the filter parameters to optimize the signal frequency response, and optimizing the model's response to differentiated signal strengths. By enhancing the model's dynamic adaptability, ensure that the model can accurately reflect signal changes in different signal environments. Construct a preliminary direction of arrival estimate. Using the improved parameters and algorithms, propose a preliminary direction of arrival estimate to ensure the accuracy and practicality of the estimate result. The formula is used:

[0123]

[0124] Among them, β represents the estimation accuracy of the direction of arrival, τi Represents the timestamp weight, S i Represents the strength of each signal point, represents the average signal strength, and n represents the number of signal points.

[0125] Specifically, if Figure 6 As shown in the figure, the steps for using the preliminary DOA estimate to fine-tune the radar array direction, optimize the alignment of the transmit and receive beams, adjust the array parameters, and obtain the radar DOA estimate record are as follows:

[0126] S501: Based on the preliminary direction of arrival estimation results, the direction of the radar array is adjusted. By adjusting the array's tilt and azimuth, the array's main beam is ensured to be consistent with the target's expected direction. The execution process for obtaining radar direction adjustment data is as follows:

[0127] S501: Based on the preliminary DOA estimation results, the direction of the radar array is adjusted, including adjusting the inclination angle θ and azimuth φ of the radar array through a high-precision servo control system to ensure that the direction of the radar main beam is consistent with the target's expected direction θ. t ,φ t Alignment, continuously monitoring changes in the external environment, adjusting the array angle in real time to adapt to environmental disturbances, ensuring that the array's main beam is consistent with the target's expected direction, generating radar direction adjustment data, and recording the array's final tilt and azimuth, as well as deviations from the target direction

[0128] The improved formula is:

[0129] A=cos(θ-θ t )·cos(φ-φ t )

[0130] Among them, A represents the alignment accuracy of the radar array adjustment, θ and φ represent the inclination and azimuth of the current radar array, θ t and φ t Indicates the target's estimated inclination and azimuth.

[0131] S502: Using radar direction adjustment data, adjust the alignment accuracy of the transmit and receive beams. By fine-tuning the beam width and transmission angle, the beam coverage of the target is optimized. The execution process for generating beam alignment optimization data is as follows:

[0132] S502: Using radar direction adjustment data, adjust the alignment accuracy of the transmit and receive beams. Fine-tune the beam width W and emission angle α through a precise control system to ensure that the beam can maximize coverage of the target area. Dynamically adjust the beam width and angle based on the size and distance of the target to optimize the focusing and diffusion characteristics of the beam and optimize the beam coverage of the target. Generate beam alignment optimization data, record the optimized beam width and emission angle, and coverage effect evaluation indicators, using the formula:

[0133]

[0134] Where B represents the coverage efficiency of the beam on the target, W represents the beam width, α represents the emission angle, and d represents the distance between the target and the radar.

[0135] S503: Based on the beam alignment optimization data, the target position is locked, the radar gain and frequency response are continuously adjusted to capture the target signal, and the effectiveness of the adjustments is continuously monitored to verify the effectiveness. The execution process for obtaining radar direction of arrival estimation records is as follows;

[0136] S503: Based on the beam alignment optimization data, the target position is locked. The radar system's gain G and frequency response F are carefully adjusted to ensure accurate capture of the target signal. The basis for adjustment includes the target's movement speed and direction, as well as the impact of environmental conditions on signal propagation. The effectiveness of the adjustment is continuously monitored and verified. The effect of beam adjustment and signal capture is verified through real-time data analysis tools. The radar direction of arrival estimation record is obtained, which includes the adjusted gain and frequency response, as well as the accurate lock of the target position.

[0137] The improved formula is:

[0138] C=G·e -λF

[0139] Among them, C represents the effect index of signal capture, G represents the gain of the radar, F represents the frequency response, and λ represents the signal attenuation coefficient taking into account the influence of environmental noise and target distance.

[0140] Specifically, if Figure 7 As shown in the figure, according to the radar direction of arrival estimation record, parameter adjustment is performed, radar parameters are reconfigured, beam transmission angle and receiving sensitivity are adjusted, and the steps of generating the radar target positioning solution are as follows:

[0141] S601: Extract key data from the radar direction of arrival estimation record, including the optimal beam transmission angle and power requirement. This includes evaluating each beam angle data, determining the angle value and power output that need to be adjusted, and resetting the radar parameters based on the data. The execution process of generating the parameter adjustment record is as follows;

[0142] S601: Extract key data from radar direction-of-arrival estimation records. First, perform a detailed analysis of each recorded data point, including the optimal beam transmission angle α and power requirement P. Use advanced data processing techniques to evaluate the effect of each beam angle and determine the efficiency of beam coverage in each direction. Each beam angle data is evaluated and the angle value and power output are adjusted based on target response and environmental feedback to maximize coverage efficiency and signal quality. Based on the data, the radar parameters are reset. The automated adjustment system updates the parameters and generates a parameter adjustment record. The record includes the angle and power values ​​before and after the adjustment, as well as the corresponding effect improvement. The formula is used:

[0143]

[0144] Among them, Θ represents the radar parameter index after comprehensive adjustment, α i and P i Represent the emission angle and power requirement ω of the i-th data point respectively α and ω P Represent the weights of angle and power respectively, ω i represents the importance of the i-th data point, and n represents the number of data points.

[0145] S602: Adjust the physical position and angle of the radar transmitting antenna according to the parameter adjustment record, including fine-tuning the antenna position and electronic angle adjustment accuracy, and adjust the transmit power to the new set value. The execution process for generating the radar transmit configuration update record is as follows;

[0146] S602: Adjust the physical position and angle of the radar transmit antenna based on the parameter adjustment record, performing detailed physical and electronic adjustments, including fine-tuning the antenna position to adapt to the new transmit angle α′ and precisely controlling the angle accuracy through the electronic adjustment system. Simultaneously, adjust the transmit power to the new set value P′ to ensure that the radar system's transmit power matches the target's distance and size, thereby improving signal transmission and reception quality. Generate a radar transmit configuration update record, including the adjusted antenna position, angle, and power values, as well as the specific impact of each adjustment on system performance. The formula is:

[0147] Φ=P′·cos(α′-α)

[0148] Where Φ represents the updated radar transmission configuration effectiveness, P′ represents the newly set transmission power, and α′ and α represent the adjusted and original transmission angles, respectively.

[0149] S603: Using the radar transmission configuration update record, resetting the receiving radar parameters, including adjusting the receiving sensitivity and calibrating the filter parameters, to optimize the overall reception quality, and generating a radar target positioning solution. The execution process is as follows;

[0150] S603: Using the radar transmission configuration update record, reset the receiving radar parameters, adjust the receiving radar sensitivity S and calibration filter parameter F to adapt to the changes in the transmission configuration and external environmental conditions, optimize the overall reception quality, use advanced signal processing technology to improve the signal recognition rate of the receiving system and reduce errors, and generate a radar target positioning solution, including the adjusted receiving settings and specific operation steps to ensure that the radar system can accurately locate the target under various operating conditions. The formula is:

[0151]

[0152] Among them, Λ represents the performance index of the receiving radar after optimization, S represents the receiving sensitivity, F represents the filtering parameter, and e in the formula -F Represents a nonlinear response function in signal processing and is used to simulate the dynamic adjustment of signal filtering effects.

[0153] like Figure 8 As shown, a target direction of arrival estimation system based on array radar includes:

[0154] The radar array configuration module adjusts the scanning frequency and angle of the radar beam within the target motion area, synchronously adjusts the radar transmit and receive sensitivities, configures the radar coverage, and obtains the configured radar coverage data;

[0155] The target signal acquisition module controls the excitation of the radar beam according to the configured radar coverage data, captures the target reflection signal, records the signal timestamp and intensity, adjusts the waveform capture time and beam emission interval, and obtains the radar target signal record;

[0156] The signal feature separation module records radar target signals, analyzes key waveforms in the signals, adjusts the signal separation threshold, distinguishes target signals from ambient noise, identifies and extracts signal components that affect the direction of arrival, and obtains key signal feature data.

[0157] The direction of arrival simulation module uses key signal feature data to calculate and simulate angles and signal strengths, collates the simulation results with real-time reflection data, and optimizes the estimation accuracy to obtain direction of arrival simulation results.

[0158] The target positioning optimization module fine-tunes the radar array direction based on the direction of arrival simulation results, adjusts the beam transmission and reception alignment and locks the target position, refines and optimizes the radar parameter configuration, and obtains the radar's target positioning solution.

[0159] The above are merely preferred embodiments of the present invention and do not limit the present invention in any other form. Any technician familiar with the profession may use the technical content disclosed above to change or modify it into an equivalent embodiment with equivalent changes and apply it to other fields. However, any simple modification, equivalent change and modification made to the above embodiment based on the technical essence of the present invention without departing from the content of the technical solution of the present invention shall still fall within the scope of protection of the technical solution of the present invention.

Claims

1. A target direction of arrival estimation method based on array radar, characterized in that: The following steps are involved: Set the frequency and angle of the radar beam scan, adjust the radar array's transmit angle and receive sensitivity, cover the target's motion area, match the signal coverage range with the target's preset motion pattern, and obtain the radar coverage configuration; Using the radar coverage configuration, directionally exciting the radar beam, capturing the target's reflected signal, recording the signal's timestamp and intensity, calibrating the waveform capture time and the beam emission interval, and obtaining a target reflected signal record; By analyzing the target reflection signal record, identifying the signal waveform associated with the target motion, adjusting the signal separation threshold, separating the target signal from the ambient noise, and obtaining key signal waveform features; Analyze the key signal waveform characteristics, calculate the signal reflection strength at different angles, compare the simulated reflection results with the real-time reflection data, and obtain a preliminary direction of arrival estimation result; Using the preliminary direction of arrival estimate, fine-tune the direction of the radar array, optimize the alignment of transmit and receive beams, adjust array parameters, and obtain radar direction of arrival estimate records; According to the radar direction of arrival estimation record, parameter adjustment is performed, radar parameters are reconfigured, beam emission angle and receiving sensitivity are adjusted, and a radar target positioning solution is generated.

2. The target direction of arrival estimation method based on array radar according to claim 1, characterized in that: The radar coverage configuration includes scanning frequency setting, transmission angle adjustment, and receiving sensitivity configuration; the target reflection signal record includes time stamp, signal strength level, and waveform time comparison; the key signal waveform characteristics include signal threshold setting, target signal extraction, and environmental noise identification; the preliminary direction of arrival estimation results include angle difference measurement, reflection intensity measurement, and simulation data comparison; the radar direction of arrival estimation record includes direction fine-tuning, beam alignment accuracy, and parameter optimization configuration; the radar target positioning solution includes beam angle adjustment, sensitivity level, and radar parameter reset.

3. The target direction of arrival estimation method based on array radar according to claim 1, characterized in that: Set the frequency and angle of the radar beam scan, adjust the radar array's transmit angle and receive sensitivity, cover the target's motion area, and match the signal coverage range with the target's preset motion pattern. The steps for obtaining radar coverage configuration are as follows: Set the frequency and angle of the radar beam scan, adjust the scan angle to match the size of the monitoring area, and obtain radar configuration parameters by adjusting the radar transmission angle and receiving sensitivity to match the target motion characteristics; Using the radar configuration parameters, fine-tuning the radar's frequency response, and by real-time analyzing the degree of match between the coverage range and the target's preset motion pattern, adjusting signal processing parameters and optimizing coverage effects, thereby generating radar coverage range matching data; Through the radar coverage matching data, signal detection adjustment is performed, target dynamics in the coverage area are analyzed, signal coverage is matched with target behavior, and radar coverage configuration is obtained.

4. The target direction of arrival estimation method based on array radar according to claim 1, characterized in that: The steps of utilizing the radar coverage configuration, directionally stimulating the radar beam, capturing the target's reflected signal, recording the signal's timestamp and intensity, and calibrating the waveform capture time and beam emission interval to obtain the target's reflected signal record are as follows: Based on the radar coverage configuration, directionally configure radar beam parameters, including beam width and frequency modulation, optimize beam angle and output power, optimize beam capture efficiency, and generate a beam configuration record; Using the beam configuration recording, capturing radar signals reflected from multiple angles, recording the timestamp and strength of each signal, adjusting the sensitivity of the receiving antenna and the gain of the signal amplifier to optimize the quality and reliability of the signal, and obtaining a record of the reflected signal; The reflected signal record is used to calibrate the signal time, adjust the filter and noise suppression parameters in the signal processor, match the signal strength and time stamp, and construct the target reflected signal record.

5. The target direction of arrival estimation method based on array radar according to claim 1, characterized in that: The steps of analyzing the target reflection signal record, identifying the signal waveform associated with the target motion, adjusting the signal separation threshold, separating the target signal from the ambient noise, and obtaining the key signal waveform features are as follows: Based on the target reflection signal records, frequency and timestamp analysis is performed to screen signal waveforms that match the target movement frequency, and by comparing the amplitude and phase information of the waveforms, key waveforms associated with the target position change are identified to generate a key waveform data set; Using the key waveform data set, adjusting the separation threshold of the signal processor, separating the target signal from the ambient noise, and obtaining a purified target signal; By using the purified target signal and cross-correlation analysis technology, the delay and intensity changes of the signal in the time series are analyzed, the key signal components that determine the direction of arrival are extracted, the analysis results are made to correspond to the target movement dynamics, and the key signal waveform characteristics are obtained.

6. The target direction of arrival estimation method based on array radar according to claim 5, characterized in that: The formula for the cross-correlation analysis technique is as follows: Where R(τ) is the weighted cross-correlation coefficient, x(t) and y(t) are the signals in the time series, τ is the time delay parameter, N is the length of the time series, w(t) is the weight at time point t, and α is the attenuation factor.

7. The target direction of arrival estimation method based on array radar according to claim 1, characterized in that: The steps of analyzing the key signal waveform characteristics, calculating the signal reflection intensity at different angles, comparing the simulated reflection results with the real-time reflection data, and obtaining the preliminary direction of arrival estimation result are as follows: Based on the key signal waveform characteristics, the angle range is set and the simulation parameters are adjusted, the reference signal strength at each angle is adjusted, a simulation calculation of the reflection strength is performed for each angle, the simulator is adjusted to reflect the actual environmental conditions, and a simulated angle reflection record is generated; Using the simulated angle reflection record to compare with the real-time captured reflection data, including setting comparison parameters, adjusting the time window and data sampling frequency, matching the simulated data with the real-time data, and generating a data comparison analysis record; Based on the data comparison and analysis records, key parameters in the signal analysis model are adjusted, including adjusting the signal reception threshold and filtering parameters, optimizing the model's response to differentiated signal strengths, and constructing a preliminary direction of arrival estimation result.

8. The target direction of arrival estimation method based on array radar according to claim 1, characterized in that: The steps for using the preliminary DOA estimation results to fine-tune the direction of the radar array, optimize the alignment of the transmit and receive beams, adjust array parameters, and obtain radar DOA estimation records are as follows: Based on the preliminary direction of arrival estimation result, the direction of the radar array is adjusted, and by adjusting the inclination and azimuth of the array, the main beam of the array is determined to be consistent with the expected direction of the target, thereby obtaining radar direction adjustment data; Using the radar direction adjustment data, adjusting the alignment accuracy of the transmit and receive beams, optimizing the beam coverage of the target by fine-tuning the beam width and the transmit angle, and generating beam alignment optimization data; Based on the beam alignment optimization data, the target position is locked, the target signal is captured by continuously adjusting the gain and frequency response of the radar, and the effectiveness of the adjustment is continuously monitored and verified to obtain the radar direction of arrival estimation record.

9. The target direction of arrival estimation method based on array radar according to claim 1, characterized in that: The steps of adjusting parameters, reconfiguring radar parameters, adjusting beam transmission angle and receiving sensitivity, and generating a radar target positioning solution based on the radar direction of arrival estimation record are as follows: Extracting key data from the radar direction of arrival estimation record, including the optimal beam transmission angle and power requirement, including evaluating each beam angle data, determining the angle value and power output that need to be adjusted, resetting radar parameters based on the data, and generating a parameter adjustment record; Adjusting the physical position and angle of the radar transmitting antenna according to the parameter adjustment record, including fine-tuning the antenna position and electronic adjustment angle accuracy, and adjusting the transmitting power to a new set value, thereby generating a radar transmitting configuration update record; The radar transmission configuration update record is used to reset the receiving radar parameters, including adjusting the receiving sensitivity and calibrating the filtering parameters, to optimize the overall reception quality and generate a radar target positioning solution.

10. A target direction of arrival estimation system based on array radar, characterized in that: The target direction of arrival estimation method based on array radar according to any one of claims 1 to 9, wherein the system comprises: The radar array configuration module adjusts the scanning frequency and angle of the radar beam within the target motion area, synchronously adjusts the radar transmit and receive sensitivities, configures the radar coverage, and obtains the configured radar coverage data; The target signal acquisition module controls the excitation of the radar beam according to the configured radar coverage data, captures the target reflection signal, records the signal timestamp and intensity, adjusts the waveform capture time and the beam emission interval, and obtains the radar target signal record; The signal feature separation module records the radar target signal, analyzes the key waveform in the signal, adjusts the signal separation threshold, and distinguishes the target signal from the environmental noise to obtain key signal feature data; The direction of arrival simulation module uses the key signal characteristic data to calculate and simulate the angle and signal strength, calibrates the simulation results with the real-time reflection data and optimizes the estimation accuracy to obtain the direction of arrival simulation results; The target positioning optimization module fine-tunes the radar array direction based on the DOA simulation results, adjusts the beam transmission and reception alignment, locks the target position, refines the radar parameter configuration, and obtains the radar's target positioning solution.

Images