CN113970739A - Empty pipe primary radar self-adaptive wind power plant clutter recognition and suppression method - Google Patents
Empty pipe primary radar self-adaptive wind power plant clutter recognition and suppression method Download PDFInfo
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Abstract
The invention discloses a method for recognizing and inhibiting clutter of an air traffic control primary radar self-adaptive wind power plant, which comprises the following steps: receiving and storing primary radar original echo, primary radar point track data and secondary radar track data; performing azimuth distance gridding in a primary radar detection area, analyzing the primary radar data quality in a grid, and identifying an abnormal area; performing feature extraction in an abnormal region by using original echo data of a radar and track data of radar points, and identifying a clutter region of a wind power plant; aiming at the regional characteristics of the wind power plant, selecting a wind power plant clutter suppression technology, and adaptively optimizing clutter suppression parameters; the method comprises the steps of carrying out quantitative evaluation on the optimization effect, iterating optimization strategies and parameters until the optimization effect meets the radar detection performance index requirement, adjusting clutter suppression parameters by adaptively selecting a wind farm clutter suppression means, evaluating radar detection performance after clutter suppression, and greatly improving radar detection performance under the clutter interference of the wind farm.
Description
Technical Field
The invention relates to the technical field of air traffic control radars, in particular to a method for recognizing and suppressing clutter of an air traffic control primary radar self-adaptive wind power plant.
Background
With the development of urbanization, the supply of traditional fossil energy such as coal is gradually tense, and the environmental problem is increasingly prominent. Wind power generation is regarded as a pollution-free and low-cost power industry, is valued by countries all over the world, and simultaneously, with the development of modern technologies, the wind power generation technology is gradually mature, so that the wind power generation technology has large-scale development and commercialized development conditions. In recent years, the wind turbine installation amount worldwide has exponentially increased. However, a wind turbine in a wind farm generally comprises blades, a nacelle and a mast, the height of the wind turbine reaches hundreds of meters, the radar Reflection Cross Section (RCS) is large, and meanwhile, the rotating blades generate continuously-changing doppler velocity in a frequency domain, which causes target shielding, false target influence and the like on a radar, and thus the radar false alarm probability is increased or the detection probability is reduced.
The air traffic control radar is a low-resolution two-coordinate radar, and is difficult to identify the wind farm clutter through height and distance information. The traditional clutter suppression means of the air traffic control radar, such as pulse compression, AMTD and automatic constant false alarm, cannot suppress the clutter of the wind power plant. Target detection above or nearby the wind power plant can be affected by wind power plant clutter, so that radar detection performance is reduced, and air traffic safety can be seriously affected. The existence of the wind power plant influences the performance of the built radar station on one hand and brings difficulty to site selection of a newly-built radar station on the other hand.
According to the traditional wind farm clutter suppression method of the air traffic control radar, the wind farm position needs to be marked manually in the radar detection range, and the marking difficulty of the wind farm position is increased along with the increase of the deployment number of the wind farm. The degree of influence of the wind farm on the radar is related to the following conditions:
1. the scale and number of wind farms;
2. relative positions of the wind power plant and the radar;
3. radar parameters.
The clutter suppression means of the wind power plant relates to the whole radar processing flow, simultaneously relates to different processing optimization parameters according to different influence degrees, and is complex in manual setting.
Disclosure of Invention
The invention aims to provide a method for identifying and suppressing clutter of a wind power plant by an empty-pipe primary radar self-adaption.
The purpose of the invention can be realized by the following technical scheme:
a clutter recognition and suppression method for an empty pipe primary radar self-adaptive wind power plant comprises the following steps:
s1, receiving and storing primary radar original echo data, primary radar track data and secondary radar track data;
the system comprises a coordinate system, a fusion center, a plurality of sensors and a plurality of sensors, wherein the coordinate system takes the fusion center as a reference point, the detection data of each sensor is uniformly synchronized to the processing period of fusion processing, and the measurement data of the sensors and the processing time-space accuracy of the fusion center are finished;
s2, performing azimuth distance gridding in the primary radar detection area, analyzing the primary radar data quality in the grid, and identifying the radar detection performance abnormal area;
s2-1, gridding the primary radar detection range according to M distance units and N azimuth sectors, and establishing index values for grid units;
s2-2, performing data quality analysis on the divided grid units, calculating type performance indexes in grid regions, and selecting evaluation indexes as detection probability, false alarm rate and flight path errors for abnormal region judgment aiming at the influence of wind farm clutter on radar performance;
s2-3, performing comprehensive regional quality scoring according to the calculated detection probability Pd, false alarm rate Pf and track error D, setting a detection probability qualified index Pdth, a false alarm rate qualified index Pfth and a track error qualified index Dth, judging as a normal region when the detection probability in the grid region is greater than the index Pdth, the false alarm rate is less than the index Pfth and the track error is less than the index Dth, and judging as an abnormal region in the rest regions;
s2-4, storing the area index, the attribute and the area performance index parameter;
s3: aiming at the detection performance abnormal area, performing feature extraction on the abnormal area by using original echo data of a radar and track data of radar points, and identifying a clutter area of the wind power plant;
s3-1, if the wind power plant is not in the radar sight distance range, the radar is not affected, the radar is used as the center, the radar sight distance range is calculated in the radar coverage range based on the geographical position altitude and the size of the wind turbine, the abnormal area is located in the sight distance range and is identified and stored, the next step of identification is carried out, and otherwise, the abnormal area is not the wind power plant clutter area;
s3-2, carrying out saturation detection on the abnormal area in the range of the distance, if the area is not saturated, carrying out identification and storage, carrying out next identification, if the area is saturated, identifying the saturated distance unit in the area as a saturated area, and setting an STC curve for attenuation according to the saturation condition;
s3-3, extracting original echo characteristics of the unsaturated abnormal region, performing spectrum analysis on echoes of each distance unit in the region after accumulating multiple frames, identifying the region with broadened echo Doppler spectrum as a wind farm clutter region, and identifying the distance unit where wind farm clutter is located;
s4, self-adaptively selecting a wind farm clutter suppression strategy and parameters according to the comprehensive performance index of the identified wind farm clutter region, and performing wind farm clutter suppression;
the clutter suppression method of the wind farm relates to radar signal processing, radar point trace processing and radar data processing, and the selectable clutter suppression means for the clutter of the wind farm comprises a self-adaptive scanning technology, a wind farm signal clearing algorithm, a sub-channel high-resolution clutter map, an enhanced CFAR, a point trace filtering algorithm and a track self-adaptive tracking filtering algorithm;
aiming at different influences and influence degrees of wind farm clutter on the radar, a wind farm clutter suppression strategy table is established, 6 wind farm clutter suppression means are arranged and combined to form an influence type-suppression strategy table, and a corresponding suppression strategy is selected according to comprehensive performance indexes of wind farm clutter areas;
a wind power plant clutter removing algorithm, a sub-channel high-resolution clutter map and a point trace filtering algorithm are indispensable options;
s5, evaluating the performance of the wind power plant clutter region measured by adopting anti-interference suppression, wherein the evaluation indexes are detection probability improvement rate, false alarm probability improvement rate and track error improvement rate, the improvement performance reaches a set threshold, ending the optimization, otherwise, optimizing the optimized measurement and parameters, and iterating the anti-wind power plant interference effect.
The invention has the beneficial effects that:
(1) according to the method, the clutter area and the influence type of the wind farm are identified by analyzing the radar data quality and extracting the clutter characteristic parameters of the wind farm, the influence degree of the wind farm on the radar performance is quantized, the influence of the wind farm clutter is relieved by the optimized parameters of a self-adaptive iterative wind farm suppression means, and the radar detection performance is improved;
(2) the software processing method realizes clutter suppression of the wind power plant on the premise of not changing hardware;
(3) according to the method, radar data quality is evaluated, abnormal areas are analyzed and detected, area characteristic parameters are extracted, and a wind power plant clutter area is automatically identified;
(4) according to the method, the wind power plant inhibition optimization parameters are selected in a self-adaptive mode, iterative comparison operation is carried out on the optimization result, and the radar performance is improved. The manual operation of the user is reduced, and the experience is improved.
Drawings
The invention will be further described with reference to the accompanying drawings.
FIG. 1 is a flow chart of the system process of the present invention.
FIG. 2 is a flow chart of data quality assessment area partitioning according to the present invention.
FIG. 3 is a schematic diagram of gridding the detection range according to the present invention.
FIG. 4 is a flow chart of wind farm clutter region discrimination according to the present invention.
FIG. 5 is a schematic diagram of an area of the wind power plant influencing the empty pipe radar.
FIG. 6 is a flow chart of a wind farm signal cleaning algorithm of the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, the invention relates to a method for recognizing and suppressing clutter of an air traffic control primary radar self-adaptive wind power plant, which comprises the following steps:
s1: receiving and storing primary radar original echo data, primary radar point trace data, primary radar track data and secondary radar track data,
carrying out protocol analysis on received track data, extracting target information, unifying the primary radar track data and the secondary radar track data by using a radar coordinate as a reference point, using the same coordinate system and a synchronous processing period to complete data space-time calibration, and carrying out fusion processing on the primary radar track data and the secondary radar track;
s2: as shown in fig. 2, performing azimuth distance gridding in a primary radar detection area, analyzing the primary radar data quality in a grid, and identifying an abnormal area;
s2-1, as shown in FIG. 3, gridding the primary radar detection range according to M distance units and N azimuth sectors, and establishing index values for the grid units;
s2-2, performing data quality analysis on the divided grid units, calculating type performance indexes in grid regions, and selecting evaluation indexes as detection probability, false alarm rate and flight path errors for abnormal region judgment aiming at the influence of wind farm clutter on radar performance;
the evaluation detection probability Pd is described by adopting the ratio of the total number of the fused tracks and the total number of the fused tracks in N frames to the sum of the total number of the single-secondary tracks in a data statistics time period:
wherein:
pd-false alarm rate;
n-number of evaluation data frames;
MS-number of single frame and single secondary flight path;
MT-number of single frame fusion tracks.
The estimated false alarm rate Pf is described by the ratio of the number of single flight paths in N frames to the total number of the fused flight paths in a data statistical time period;
wherein:
pf-false alarm rate;
n-number of evaluation data frames;
MF-number of single frame single flight path;
MT-number of single frame fusion tracks.
Evaluating the track error D by adopting the average value of the total errors of N frames of tracks in the data statistical time period;
wherein:
d is track error;
n-number of evaluation data frames;
dr-frame i average track error;
wherein:
dr-frame r average track error;
k is the total track number of the r frame;
r2-secondary radar track distance in the fusion track;
ΔRi-the ith point distance error in the fusion track of the r frame, the primary radar track distance minus the secondary track distance;
Δθithe ith point azimuth error in the fusion track of the r frame is subtracted from the primary radar track azimuth to the secondary track azimuth;
σRdistance system error, this example selects 60 meters;
σθthe azimuth systematic error, 1 degree was chosen for this example.
S2-3, comprehensively evaluating the regional quality according to the calculated detection probability Pd, the false alarm rate Pf and the track error D, and setting a detection probability qualification index Pdth, a false alarm rate qualification index Pfth and a track error qualification index Dth. When the detection probability in the grid area is greater than the index Pdth, the false alarm rate is less than the index Pfth, and the track error is less than the index Dth, the grid area is judged to be a normal area, and the rest areas are judged to be detection performance abnormal areas.
S2-4, storing the area index, the attribute and the area performance index parameter.
S3: as shown in fig. 4, for the detection performance abnormal region, feature extraction is performed on the abnormal region by using the original echo data of the radar and the track data of the radar point, so as to identify the clutter region of the wind farm;
s3-1, as shown in FIG. 5, if the wind power plant is not in the radar sight distance range, the radar is not affected;
the method comprises the steps that a radar is used as a center, a radar visual range is calculated in a radar coverage range based on the geographical position altitude and the size of a wind turbine, an abnormal area is located in the visual range and is identified and stored, the abnormal area is identified in the next step, and otherwise, the abnormal area is not a wind farm clutter area;
s3-2, carrying out saturation detection on the abnormal area in the range of the distance, if the area is not saturated, carrying out identification and storage, carrying out next identification, if the area is saturated, identifying the saturated distance unit in the area as a saturated area, and setting an STC curve for attenuation according to the saturation condition;
s3-3, extracting the original echo characteristics of the unsaturated abnormal region, performing spectrum analysis on the echo of each distance unit in the region after accumulating multiple frames, identifying the region with broadened echo Doppler spectrum as a wind farm clutter region, and identifying the distance unit where the wind farm clutter is located.
S4, self-adaptively selecting a wind farm clutter suppression strategy and parameters according to the comprehensive performance index of the identified wind farm clutter region, and performing wind farm clutter suppression;
the clutter suppression method of the wind power plant relates to radar signal processing, radar point trace processing and radar data processing;
the clutter suppression means selected aiming at the clutter of the wind power plant comprise a self-adaptive scanning technology, a wind power plant filtering and clearing algorithm, a sub-channel high-resolution clutter map, an enhanced CFAR, a point track filtering algorithm and a track self-adaptive tracking filtering algorithm;
aiming at different influences and influence degrees of wind farm clutter on the radar, a wind farm clutter suppression strategy table is established, 6 wind farm clutter suppression means are arranged and combined to form an influence type-suppression strategy table, and a corresponding suppression strategy is selected according to comprehensive performance indexes of wind farm clutter areas;
the method comprises the following steps of (1) selecting a wind power plant clutter removing algorithm, a sub-channel high-resolution clutter map and a point trace filtering algorithm as necessary options;
the method comprises the steps of self-adaptive scanning technology, wherein the time sequence of a transmitting pulse is adjusted in a self-adaptive mode according to position information of a clutter area of a wind power plant, the splicing position of long and short pulses is changed, narrow pulses and high repetition frequency pulse strings are used for distance coverage, a radar for empty management at one time usually adopts a long and short pulse splicing mode for distance coverage, the width of the long pulse is usually 100us in ASR (asynchronous receiver resonance) and is usually 300us in ARSR (auto ranging response) for the wind power plant, the pulse pressure of the long pulse is farther from the side lobe influence range and is not beneficial to target detection, the influence of the wind power plant on the radar is concentrated at a closer distance, the splicing position of the long and short pulses is changed, the short pulses are used for short-distance coverage to the maximum extent, and the influence of the wind power plant on the radar is reduced;
when the wind farm clutter exists in the detection range, the wind turbines in the wind farms have larger RCS, the generated echo signals are high in amplitude, the signal frequency spectrum is widened due to the rotation of blades of the wind turbines, when the target signals and the wind farm echo signals are in the same or adjacent distance units, the wind farm echo signals cover the target signals, the wind farm echo signals are inverted, and the wind farm signals are cleared in the original echo by using a clearing algorithm, so that the effect of inhibiting the wind farm is achieved;
as shown in fig. 6, the wind farm clutter removal algorithm extracts the amplitude and phase of the original echo signal of the distance unit where the wind farm clutter is located according to the wind farm clutter area identified in the abnormal area analysis and the distance unit identification where the wind farm clutter is located, inverts the wind farm signal, and determines whether the pulse pressure side lobe is reduced after subtracting the inversion signal from the original echo signal, and when the side lobe is reduced, the next process is performed, and when the side lobe is not reduced, the signal inversion and removal are continued;
a sub-channel high-resolution clutter map, wherein for each scanning period, each channel output of the AMTD is used for updating the self-adaptive clutter map, a specified false alarm rate is ensured to be obtained according to the fact that a clutter level estimated in the clutter map is used as a threshold value of an output end of the AMTD filter, the sub-channel high-resolution clutter map is mainly used for sub-channel filter target echo super-clutter detection, and the resolution ratio of the self-adaptive clutter map is one pulse group multiplied by one distance quantization unit;
the traditional CFAR algorithm compares a detection unit with the average value or the selected value of the peripheral reference units to obtain a detection result, when the clutter of the wind farm exists, the echo amplitude of the clutter of the wind farm is large, so that the detection threshold of the CFAR can be improved, relatively weak target signals cannot pass through the threshold and are missed to be detected, the CFAR is enhanced, the unit with the amplitude larger than a certain threshold value in the reference unit is subjected to interframe matching and counting, when the N/M criterion is met, the CFAR is calculated, the average noise level is adopted for replacement, N usually selects 3 frames, and M usually selects 5 frames;
the point trace filtering algorithm is to the point trace characteristics that the wind power plant echo produces, carry out wind power plant point trace suppression, in order to eliminate wind power plant clutter surplus in the abnormal region, the position information (distance and position) that wind power plant clutter point trace appears is basically unchanged or changes very little, and not every frame all appears, and the echo that forms the point trace has Doppler speed and widens, the characteristics such as height is in low latitude, to such characteristic, carry out interframe matching based on regional RAG picture in the abnormal region, if can match, carry out interframe count, then carry out the criterion extraction according to the mode of interframe sliding window, the clutter target that satisfies certain criterion scope can be judged as fixed clutter, specifically be:
the first step is as follows: dividing a plurality of processing units in the abnormal area according to the distance and the direction;
the second step is that: performing trace point quality evaluation on each target trace point in the processing unit by referring to three elements of relative amplitude of trace point formation, frequency spectrum information of trace point, height estimation value of trace point and the like;
the third step: and judging whether the target track parameter accords with the characteristics of the wind power plant clutter or not, wherein the accorded track is marked as 'wind power plant echo track', and is not used for subsequent track correlation processing.
When clutter of the wind power plant exists, the residual point tracks of the wind power plant are increased, and the phenomenon that the track drifts and even starts again when the target passes through the wind power plant area is caused by the reduction of the target point tracks. The track self-adaptive tracking model is used for carrying out track processing on a wind power plant clutter region by adopting an enhanced correlation algorithm and a multi-interaction tracking model, so that the multi-target tracking performance of the wind power plant clutter region is improved.
S5: and performing performance evaluation on the clutter region of the wind power plant adopting the anti-interference suppression measurement, wherein the evaluation indexes are the detection probability improvement rate, the false alarm probability improvement rate and the track error improvement rate, the improvement performance reaches a set threshold value, and ending the optimization, otherwise, optimizing the measurement and parameters and iterating the anti-wind field interference effect.
While one embodiment of the present invention has been described in detail, the description is only a preferred embodiment of the present invention and should not be taken as limiting the scope of the invention. All equivalent changes and modifications made within the scope of the present invention shall fall within the scope of the present invention.
Claims (10)
1. A clutter recognition and suppression method for an empty pipe primary radar self-adaptive wind power plant is characterized by comprising the following steps:
s1: receiving and storing primary radar original echo, primary radar point track data and secondary radar track data;
s2: performing azimuth distance gridding in a primary radar detection area, analyzing the primary radar data quality in a grid, and identifying an abnormal area;
s3: performing feature extraction in an abnormal region by using original echo data of a radar and track data of radar points, and identifying a clutter region of a wind power plant;
s4: aiming at the regional characteristics of the wind power plant, selecting a wind power plant clutter suppression technology, and adaptively optimizing clutter suppression parameters;
s5: and carrying out quantitative evaluation on the optimization effect, and iterating the optimization strategy and parameters until the radar detection performance index requirement is met.
2. The method for recognizing and suppressing clutter of an empty-pipe primary radar adaptive wind farm according to claim 1, wherein in S2, a primary radar detection area is gridded according to M distance units and N azimuth sectors, and index values are established for grid units;
and performing data quality analysis on the divided grid units, calculating type performance indexes in the grid area, and selecting evaluation indexes as detection probability, false alarm rate and flight path error to perform abnormal area judgment.
3. The method for recognizing and suppressing clutter of an air traffic control primary radar adaptive wind power plant according to claim 2, wherein region quality comprehensive scoring is performed according to the calculated detection probability Pd, false alarm rate Pf and track error D, a region meeting index requirements is judged to be a normal region, and the other regions are judged to be abnormal regions.
4. The method for recognizing and suppressing clutter of an air traffic control primary radar adaptive wind farm according to claim 1, wherein the clutter suppression means selected for the clutter of the wind farm in S4 comprises an adaptive scanning technique, a wind farm clutter removal algorithm, a sub-channel high resolution clutter map, an enhanced CFAR, a point track filtering algorithm and a track adaptive tracking filtering algorithm;
aiming at different influences and influence degrees of wind farm clutter on the radar, a wind farm clutter suppression strategy table is established, 6 wind farm clutter suppression means are arranged and combined to form an influence type-suppression strategy table, and a corresponding suppression strategy is selected according to comprehensive performance indexes of wind farm clutter areas.
5. The method for recognizing and suppressing clutter of an empty-pipe primary radar adaptive wind farm according to claim 4, wherein the adaptive scanning technology is to adaptively adjust the timing sequence of the transmitted pulses according to the clutter region position information of the wind farm, change the long-short pulse distance splicing position, and use the narrow pulse and the high repetition frequency pulse train for long-distance coverage.
6. The method for recognizing and suppressing the clutter of the wind farm adaptively by the air traffic control primary radar according to claim 4, wherein the clutter removal algorithm of the wind farm is to extract the amplitude and the phase of the original echo signal of the distance unit where the clutter of the wind farm is located according to the wind farm clutter area identified in the abnormal area analysis and the distance unit identification where the clutter of the wind farm is located, invert the wind farm signal, judge whether the pulse pressure sidelobe is reduced after subtracting the inversion signal from the original echo signal, perform the next process when the sidelobe is reduced, and continue to invert and remove the signal when the sidelobe is not reduced.
7. The adaptive wind farm clutter recognition and suppression method according to claim 4, wherein a sub-channel high resolution clutter map is used to update the adaptive clutter map for each scan cycle for each channel output of the AMTD, and the estimated clutter level in the clutter map is used as the threshold value at the output of the AMTD filter to ensure that the specified false alarm rate is achieved, primarily for sub-channel filter target echo super-clutter detection, and the resolution of the adaptive clutter map is one pulse group multiplied by a distance quantization unit.
8. The method for recognizing and suppressing clutter of an empty-pipe primary radar adaptive wind farm according to claim 4, wherein the enhanced CFAR is performed by performing interframe matching and counting of units with amplitudes greater than a certain threshold value in a reference unit, and when an N/M criterion is met, the CFAR is calculated and replaced by an average noise level.
9. The method for recognizing and suppressing clutter of an air-managed primary radar self-adaptive wind power plant according to claim 4, wherein a point trace filtering algorithm is used for performing inter-frame matching based on a regional RAG (RAG-g) graph in an abnormal region, inter-frame counting is performed in the matching process, then criterion extraction is performed in an inter-frame sliding window mode, and clutter targets meeting a certain criterion range can be determined as fixed clutter.
10. The method for recognizing and suppressing clutter of an air traffic control primary radar adaptive wind farm according to claim 1, wherein S5 comprises performing performance evaluation on a clutter region of the wind farm measured by anti-interference suppression, wherein the evaluation indexes are a detection probability improvement rate, a false alarm probability improvement rate and a track error improvement rate;
namely, the improvement performance reaches a set threshold value, the optimization is finished, otherwise, the optimization measurement and parameters are optimized, and the interference effect of the wind-resistant electric field is iterated.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114510846A (en) * | 2022-04-18 | 2022-05-17 | 天津航大天元航空技术有限公司 | Safety assessment method and device for wind power plant and electronic equipment |
| CN116299304A (en) * | 2023-05-19 | 2023-06-23 | 北京敏视达雷达有限公司 | Wind power clutter filtering method, device, equipment and readable storage medium |
| CN116990773A (en) * | 2023-09-27 | 2023-11-03 | 广州辰创科技发展有限公司 | Low-speed small target detection method and device based on self-adaptive threshold and storage medium |
| CN117970251A (en) * | 2024-03-28 | 2024-05-03 | 安徽隼波科技有限公司 | Dynamic detection method for safety radar clutter area |
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2021
- 2021-09-13 CN CN202111069548.8A patent/CN113970739A/en active Pending
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN114510846A (en) * | 2022-04-18 | 2022-05-17 | 天津航大天元航空技术有限公司 | Safety assessment method and device for wind power plant and electronic equipment |
| CN114510846B (en) * | 2022-04-18 | 2022-07-22 | 天津航大天元航空技术有限公司 | Safety assessment method and device for wind power plant and electronic equipment |
| CN116299304A (en) * | 2023-05-19 | 2023-06-23 | 北京敏视达雷达有限公司 | Wind power clutter filtering method, device, equipment and readable storage medium |
| CN116299304B (en) * | 2023-05-19 | 2023-08-15 | 北京敏视达雷达有限公司 | Wind power clutter filtering method, device, equipment and readable storage medium |
| CN116990773A (en) * | 2023-09-27 | 2023-11-03 | 广州辰创科技发展有限公司 | Low-speed small target detection method and device based on self-adaptive threshold and storage medium |
| CN117970251A (en) * | 2024-03-28 | 2024-05-03 | 安徽隼波科技有限公司 | Dynamic detection method for safety radar clutter area |
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