CN111060880A - Meteorological clutter suppression method based on constant false alarm detection principle - Google Patents
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Abstract
The invention discloses a meteorological clutter suppression method based on a constant false alarm detection principle, which relates to the field of radar clutter suppression and comprises the following steps: acquiring all echo signal frequency spectrums output after the first constant false alarm detection processing; sequentially selecting frequency points to be detected from effective frequency spectrums of all echo signal frequency spectrums and recording the power of the frequency points to be detected; respectively arranging a first detection window, a second detection window, a third detection window and a fourth detection window on two sides of a frequency point to be detected in a speed dimension and a distance dimension, and carrying out power sampling of echo amplitude on each frequency point in the windows; if the power of the frequency point to be measured is larger than the sum of the average power of all windows and a preset threshold value, reserving the frequency point to be measured, and otherwise, filtering the frequency point to be measured; through the second time constant false alarm detection and target screening filtration of this application, carry out amplitude detection, comparison and identification processing to each frequency point that awaits measuring on speed dimension and distance dimension, weather clutter such as cloud and rain filters in advance, makes it can not get into the follow-up target tracking processing link.
Description
Technical Field
The invention relates to the field of radar clutter suppression, in particular to a weather clutter suppression method based on a constant false alarm detection principle.
Background
At present, aiming at important facilities, key sites and low-altitude airspaces around important areas, a microwave radar is adopted to detect and track low-altitude/ultra-low-altitude flying targets, all-weather and all-airspace provides monitoring and early warning of low-altitude, slow speed, danger and small target invasion of flying birds or unmanned machines, and the market demand on the aspect is urgent and the prospect is very wide. In a low-altitude airspace, when a microwave radar mainly detects and processes echo signals of low, small and slow intrusion targets, a large amount of stray interference with similar echo signal characteristics is accompanied, wherein the distribution range and echo characteristic parameters of weather targets such as moving cloud rain and air mass are particularly similar to those of really detected and tracked intrusion targets, and the number of formed false alarm signals is particularly large due to close correlation with weather conditions, strong randomness and numerous, so that the generated negative effects are particularly large.
Disclosure of Invention
The invention provides a meteorological clutter suppression method based on a constant false alarm detection principle aiming at the problems and the technical requirements. The technical scheme of the invention is as follows:
a weather clutter suppression method based on a constant false alarm detection principle comprises the following steps:
s1, obtaining echo signal frequency spectrums after first constant false alarm rate detection processing, wherein the echo signal frequency spectrums comprise frequency spectrums of echo signals of an invasive target, a meteorological cloud and rain target and a static target, and the echo signal frequency spectrums comprise frequency spectrums of the echo signals in a speed dimension, a distance dimension and an amplitude dimension;
s2, sequentially selecting each frequency point in an effective frequency spectrum as a frequency point to be detected, and determining the power of the frequency point to be detected according to the echo amplitude of the frequency point to be detected in the amplitude dimension, wherein the effective frequency spectrum comprises the frequency spectrum corresponding to the echo signal of the static target and the frequency spectrum corresponding to the echo signal of each target in the radar blind area and other echo signal frequency spectrums;
s3, sampling frequency points on two sides of a frequency point to be detected in the echo signal frequency spectrum in the speed dimension through a first detection window and a second detection window in the amplitude dimension, wherein the first detection window and the second detection window are spaced from the frequency point to be detected at the same distance in the speed dimension;
sampling frequency points which are positioned at two sides of a frequency point to be detected in a distance dimension in an echo signal frequency spectrum by a third detection window and a fourth detection window in an amplitude dimension, wherein the third detection window and the fourth detection window are spaced from the frequency point to be detected by the same distance in the distance dimension;
s4, determining first detection window power according to the echo amplitude of each frequency point sampled by a first detection window, determining second detection window power according to the echo amplitude of each frequency point sampled by a second detection window, determining third detection window power according to the echo amplitude of each frequency point sampled by a third detection window, and determining fourth detection window power according to the echo amplitude of each frequency point sampled by a fourth detection window;
s5, detecting whether the requirements are met
Wherein, PwTo be the power of the frequency point to be measured, PjTo preset a threshold value, Pz1Is the first detection window power, Pz2For the second detection window power, Pz3For the third detection window power, Pz4For the fourth detection window power, k1Is a weighting parameter, k, corresponding to the first detection window2For the weighting parameter, k, corresponding to the second detection window3For the weighting parameter, k, corresponding to the third detection window4Weighting parameters corresponding to the fourth detection window;
s6, if yes, reserving the frequency point to be tested; and if not, filtering the frequency point to be measured.
The further technical scheme is that the method also comprises the following steps:
respectively arranging a first window and a second window at the positions, which are positioned at the two sides of the frequency point to be detected in the speed dimension and have the same distance with the frequency point to be detected, in the echo signal frequency spectrum;
if the first window and the second window do not cover the echo signal corresponding to the static target, determining that the first window is a first detection window and determining that the second window is a second detection window;
and if the second window covers the echo signal corresponding to the static target, forming a second detection window in the area of the second window where the echo signal corresponding to the static target is removed, and extending the first window reversely relative to the second window to form a first detection window, wherein the total width of the first detection window and the second detection window is equal to the total width of the first window and the second window.
The further technical scheme is characterized in that the first window and the second window have equal width in a speed dimension and 4 speed threshold values, and have equal width in a distance dimension and 5-8 distance threshold values.
The further technical scheme is that the method also comprises the following steps:
respectively arranging a third window and a fourth window at the positions, which are positioned at the two sides of the frequency point to be detected in the distance dimension and have the same distance with the frequency point to be detected, in the echo signal frequency spectrum;
if the third window and the fourth window do not cover the echo signals of all the targets in the blind area, determining that the third window is a third detection window and determining that the fourth window is a fourth detection window;
if the fourth window covers the echo signals of all the targets in the blind area, the area of the fourth window where the echo signals of all the targets in the blind area are removed forms a fourth detection window, the third window is reversely extended relative to the fourth window to form a third detection window, and the total width of the third detection window and the total width of the fourth detection window are equal to the total width of the third window and the fourth window.
The further technical scheme is that the third window and the fourth window are equal in width in a speed dimension and are 3-6 speed threshold values, and are equal in width in a distance dimension and are 5 distance threshold values.
The further technical scheme is that the method also comprises the following steps:
protection windows are respectively arranged on two sides of a frequency point to be detected on a speed dimension and a distance dimension in an echo signal frequency spectrum, the width of each protection window on the speed dimension is equal to the distance between the frequency point to be detected and the first detection window and the second detection window on the speed dimension, and the width is 1-2 speed threshold values; the width of each protection window in the distance dimension is equal to the distance between the frequency point to be detected and the third detection window and the fourth detection window in the distance dimension, and the width is 1-2 distance gate values.
The further technical scheme is that the method also comprises the following steps:
detecting whether the echo amplitude of the amplitude dimension of each frequency point in the echo signal frequency spectrum is smaller than a first preset power threshold value and reaches a second preset power threshold value;
if the echo amplitude reaches a first preset power threshold value, determining that the frequency point belongs to an echo signal corresponding to a static target;
and if the echo amplitude is smaller than a second preset power threshold value, determining that the frequency point belongs to the echo signal of each target in the blind area.
The beneficial technical effects of the invention are as follows:
the application discloses a meteorological clutter suppression method based on a constant false alarm detection principle, which is a special detection processing method of a ground defense radar designed for monitoring and early warning of low, small and slow dangerous intrusion targets. According to the method, a second special constant false alarm detection process is performed mainly aiming at the difference between the echo characteristics of an intrusion target and the echo characteristics of weather cloud rain, all echo signal frequency spectrums output after the first constant false alarm detection process are obtained, all frequency points are sequentially selected from effective frequency spectrums to be used as frequency points to be detected, after the power of the frequency points to be detected is determined through characteristic frequency spectrum analysis, the average power of the echo amplitude of each frequency point in a window can be effectively obtained through detection windows arranged in the speed dimension and the distance dimension, and in addition, whether the detection window contains a static target or not and target echo signals in a radar blind area are detected and processed, so that the feasibility of the method and the accuracy of the target discrimination are improved; through the comparison frequency point power that awaits measuring and the size of predetermineeing the sum of threshold value and average power, thereby distinguish the frequency point that awaits measuring and filter for meteorological cloud and rain target, make it can not get into the processing link of back level target tracking, can prevent to carry out range echo collection to frequency point self that awaits measuring through the protection window that sets up respectively in speed dimension and distance dimension, make short range defence radar can trail and discriminate the target more effectively, select really having threatened low, little, the invasion target slowly, the false alarm rate has been reduced, thereby the practicality of radar under all-weather operating condition has been improved.
Drawings
Fig. 1 is a three-dimensional spectral view of an echo signal of an intruding object.
Fig. 2 is a three-dimensional spectrum view of an echo signal of a weather cloud rain target.
FIG. 3 is a three-dimensional spectral view of echo signals of an intruding target, a weather cloud rain target, and other clutter.
Fig. 4 is a flowchart of a weather clutter suppression method based on the constant false alarm detection principle disclosed in the present application.
Fig. 5 is a distribution diagram of the detection window, the protection window and the frequency point to be measured in the speed and distance dimensions disclosed in the present application.
Detailed Description
The following further describes the embodiments of the present invention with reference to the drawings.
In the present application, the low, small, and slow intrusion targets are analyzed by taking the drone target as an example, please refer to fig. 1, which shows a three-dimensional spectrum view of an echo signal of the drone target flying toward a radar. Echo signals of a typical unmanned aerial vehicle target are represented as relatively isolated cone-shaped target points on a three-dimensional spectrum view, wherein the three-dimensional spectrum is a spectrum of a speed dimension, a distance dimension and an amplitude dimension respectively, the three-dimensional coordinates of the cone-shaped target points are (10.8486, 1885.5998 and 91.028), the positions near the cone-shaped target points 1 except an unmanned aerial vehicle spiral wing echo spectrum (which is lower than the amplitude spectrum of the cone-shaped target point 1 by more than 25 dB) with relatively small amplitude are mainly distributed as relatively uniform noise spectrums, and the echo spectrum of the unmanned aerial vehicle target is positioned on the left side or the right side of the whole three-dimensional spectrum according to different flight directions of the unmanned aerial vehicle target (flying away from or facing the radar).
Referring to fig. 2, a three-dimensional spectrum view of an echo signal of a weather cloud rain target facing radar fluttering is shown. The echo of a typical weather clutter such as cloud and rain shows a spectrogram with different shapes and blocky distribution on a frequency spectrum, because the all-weather condition of an airspace is very complex, the distance, the speed, the amplitude, the distribution thickness and the distribution range of the weather cloud and rain clutter relative to a radar are greatly different, the expression form of the spectrogram has certain convergence and also has difference, and on the same aspect, the signal power of the peak power points which meet detection conditions on the frequency spectrum of the echo signal of the weather cloud and rain clutter is far higher than the noise spectrum amplitude value and different numbers of randomly distributed peak power points exist.
Referring to fig. 3, a three-dimensional spectral view of echo signals of an intruding target, a weather cloud and rain target, and other clutter is shown. Wherein, meteorological cloud and rain target's echo signal blocking distribution, unmanned aerial vehicle target's echo signal is the isolated cone relatively, and other stray target's echo signal's amplitude value is lower relatively, and this provides probably for the resolution and the screening process of target.
In order to effectively suppress specific weather cloud and rain clutter, the weather clutter suppression method based on the constant false alarm detection principle disclosed by the application statistically analyzes the spectrogram of echo signals of a large number of weather cloud and rain targets, and summarizes the spectrogram difference between the echo signals of the large number of weather cloud and rain targets and the echo signals of real invading unmanned aerial vehicle targets, as shown in fig. 4, the method comprises the following steps:
and S1, obtaining the echo signal frequency spectrum after the first constant false alarm rate detection processing, wherein the echo signal frequency spectrum comprises the frequency spectrum of the echo signal of an invasive target, a meteorological cloud and rain target and a static target, and the echo signal frequency spectrum comprises the frequency spectrum of the echo signal in a speed dimension, a distance dimension and an amplitude dimension.
S2, sequentially selecting each frequency point in the effective frequency spectrum as a frequency point to be detected, and determining the power P of the frequency point to be detected according to the echo amplitude of the frequency point to be detected in the amplitude dimensionwAnd determining specific frequency spectrum parameters of the frequency point to be measured in the speed dimension and the distance dimension. The effective frequency spectrum comprises the frequency spectrum corresponding to the echo signal of the static target and the frequency spectrum corresponding to the echo signal of each target in the radar blind area. In the present application, a method for determining an echo signal of a stationary target and an echo signal of each target in a radar blind area is as follows:
and detecting whether the echo amplitude of the amplitude dimension of each frequency point in the echo signal frequency spectrum is smaller than a first preset power threshold value and reaches a second preset power threshold value. And if the echo amplitude reaches a first preset power threshold value, determining that the frequency point belongs to the echo signal corresponding to the static target. And if the echo amplitude is smaller than a second preset power threshold value, determining that the frequency point belongs to the echo signal of each target in the blind area.
S3, setting detection windows around the frequency point to be detected in the speed and distance dimensions, in this application, before setting the detection windows, setting protection windows around the frequency point to be detected in the speed and distance dimensions, where the distribution of the protection windows (shaded portions), the detection windows, and the frequency points to be detected is as shown in fig. 5. The specific method for setting the protection window comprises the following steps:
protection windows are respectively arranged on two sides of a frequency point to be detected on a speed dimension and a distance dimension in an echo signal frequency spectrum, the width of each protection window on the speed dimension is equal to the distance between the frequency point to be detected and the first detection window and the second detection window on the speed dimension, and the width is 1-2 speed threshold values. The width of each protection window in the distance dimension is equal to the distance between the frequency point to be detected and the third detection window and the fourth detection window in the distance dimension, and the width is 1-2 distance gate values. Because the protection window is close to the frequency point to be detected and arranged around the frequency point to be detected, the amplitude echo acquisition of the frequency point to be detected can be prevented. The specific values of the single speed threshold value and the single distance threshold value are preset values, the preset values are usually obtained according to experience, and the parameter selection principle of the speed threshold value and the distance threshold value is to ensure that the frequency point to be detected is not influenced and to effectively inhibit and process meteorological cloud and rain targets and other stray signals.
The specific method for setting the detection window comprises the following steps:
and sampling amplitude dimensions of all frequency points which are positioned at two sides of the frequency point to be detected in the echo signal frequency spectrum in the speed dimension through a first detection window and a second detection window, wherein the first detection window and the second detection window are spaced from the frequency point to be detected at the same distance in the speed dimension.
In the present application, the specific setting method of the first detection window and the second detection window is as follows:
and respectively arranging a first window and a second window at the positions which are positioned at the two sides of the frequency point to be detected in the speed dimension and have the same interval with the frequency point to be detected in the echo signal frequency spectrum, wherein the first window and the second window have the same width in the speed dimension and are 4 speed threshold values, and the first window and the second window have the same width in the distance dimension and are 5-8 distance threshold values. For example, in the present application, the first window and the second window are respectively disposed on the left side and the right side of the frequency point to be measured.
And if the first window and the second window do not cover the echo signal corresponding to the static target, determining that the first window is a first detection window and determining that the second window is a second detection window.
And if the second window covers the echo signal corresponding to the static target, forming a second detection window in the area of the second window where the echo signal corresponding to the static target is removed, and extending the first window reversely relative to the second window to form a first detection window, wherein the total width of the first detection window and the second detection window is equal to the total width of the first window and the second window. If the first window covers the echo signal corresponding to the stationary target, the principle of the processing method is the same as that of the second window, and details are not repeated herein.
And sampling frequency points on two sides of the frequency point to be detected in the echo signal frequency spectrum in the distance dimension by a third detection window and a fourth detection window, wherein the third detection window and the fourth detection window are spaced from the frequency point to be detected by the same distance in the distance dimension.
In the present application, the specific setting method of the third detection window and the fourth detection window is as follows:
and a third window and a fourth window are respectively arranged on the two sides of the frequency point to be detected in the distance dimension of the echo signal spectrum and at the same distance from the frequency point to be detected, and the third window and the fourth window have the same width in the speed dimension and are 3-6 speed threshold values, and have the same width in the distance dimension and are 5 distance threshold values. For example, in the present application, the third window and the fourth window are respectively disposed on the upper side and the lower side of the frequency point to be measured.
And if the third window and the fourth window do not cover the echo signals of all the targets in the blind area, determining that the third window is a third detection window, and determining that the fourth window is a fourth detection window.
If the fourth window covers the echo signals of all the targets in the blind area, the area of the fourth window where the echo signals of all the targets in the blind area are removed forms a fourth detection window, the third window is reversely extended relative to the fourth window to form a third detection window, and the total width of the third detection window and the total width of the fourth detection window are equal to the total width of the third window and the fourth window. If the third window covers the echo signal of each target in the blind area, the principle of the processing method is the same as that of the fourth window, and details are not repeated here.
In the present application, the positions and width parameter values of the four detection windows are empirical values obtained by performing experiments and tests on echo signals of a large number of weather cloud and rain targets, and therefore, detailed descriptions thereof are not provided in the present application.
S4, averaging according to the echo amplitude of each frequency point sampled by the first detection window, and then determining the power P of the first detection windowz1And determining the power P of the second detection window after averaging according to the echo amplitudes of the frequency points sampled by the second detection windowz2And determining the power P of the third detection window after averaging according to the echo amplitudes of the frequency points sampled by the third detection windowz3And determining the power P of the fourth detection window after averaging according to the echo amplitudes of the frequency points sampled by the fourth detection windowz4。
S5, detecting whether the requirements are met
Wherein, PwTo be the power of the frequency point to be measured, PjThe threshold value P can be selected for the first time of constant false alarm detection processingz1Is the first detection window power, Pz2For the second detection window power, Pz3For the third detection window power, Pz4For the fourth detection window power, k1Is a weighting parameter, k, corresponding to the first detection window2For the weighting parameter, k, corresponding to the second detection window3For the weighting parameter, k, corresponding to the third detection window4The weighting parameter corresponding to the fourth detection window is in the range of 0.6-1.4.
And S6, if yes, reserving the frequency point to be detected as an intrusion target, and sending the frequency spectrum data (speed position, distance position and power of the frequency point to be detected) of the three-dimensional frequency spectrum recorded in the S1 to a subsequent target tracking processing link. And if not, taking the frequency point to be detected as a false alarm signal and filtering the frequency point to be detected.
According to the method, a second special constant false alarm detection process is performed mainly aiming at the difference between the echo characteristics of an intrusion target and the echo characteristics of weather cloud rain, all echo signal frequency spectrums output after the first constant false alarm detection process are obtained, all frequency points are sequentially selected from effective frequency spectrums to be used as frequency points to be detected, after the power of the frequency points to be detected is determined through characteristic frequency spectrum analysis, the average power of the echo amplitude of each frequency point in a window can be effectively obtained through detection windows arranged in the speed dimension and the distance dimension, and in addition, whether the detection window contains a static target or not and target echo signals in a radar blind area are detected and processed, so that the feasibility of the method and the accuracy of the target discrimination are improved; through the comparison frequency point power that awaits measuring and the size of predetermineeing the sum of threshold value and average power, thereby distinguish the frequency point that awaits measuring and filter for meteorological cloud and rain target, make it can not get into the processing link of back level target tracking, can prevent to carry out range echo collection to frequency point self that awaits measuring through the protection window that sets up respectively in speed dimension and distance dimension, make short range defence radar can trail and discriminate the target more effectively, select really having threatened low, little, the invasion target slowly, the false alarm rate has been reduced, thereby the practicality of radar under all-weather operating condition has been improved.
What has been described above is only a preferred embodiment of the present application, and the present invention is not limited to the above embodiment. It is to be understood that other modifications and variations directly derivable or suggested by those skilled in the art without departing from the spirit and concept of the present invention are to be considered as included within the scope of the present invention.
Claims (7)
1. A weather clutter suppression method based on a constant false alarm detection principle is characterized by comprising the following steps:
s1, obtaining echo signal frequency spectrums after first constant false alarm rate detection processing, wherein the echo signal frequency spectrums comprise frequency spectrums of echo signals of an invasive target, a meteorological cloud and rain target and a static target, and the echo signal frequency spectrums comprise frequency spectrums of the echo signals in a speed dimension, a distance dimension and an amplitude dimension;
s2, sequentially selecting each frequency point in an effective frequency spectrum as a frequency point to be detected, and determining the power of the frequency point to be detected according to the echo amplitude of the frequency point to be detected in the amplitude dimension, wherein the effective frequency spectrum comprises the frequency spectrum corresponding to the echo signal of a static target and the frequency spectrum of other echo signals except the frequency spectrum corresponding to the echo signal of each target in a radar blind area;
s3, sampling frequency points on two sides of the frequency point to be detected in the echo signal frequency spectrum in the speed dimension in the amplitude dimension through a first detection window and a second detection window, wherein the first detection window and the second detection window are spaced from the frequency point to be detected at the same distance in the speed dimension;
sampling frequency points which are positioned at two sides of the frequency point to be detected in the distance dimension in the echo signal frequency spectrum in an amplitude dimension through a third detection window and a fourth detection window, wherein the third detection window and the fourth detection window are spaced from the frequency point to be detected at the same distance in the distance dimension;
s4, determining first detection window power according to the echo amplitude of each frequency point sampled by the first detection window, determining second detection window power according to the echo amplitude of each frequency point sampled by the second detection window, determining third detection window power according to the echo amplitude of each frequency point sampled by the third detection window, and determining fourth detection window power according to the echo amplitude of each frequency point sampled by the fourth detection window;
s5, detecting whether the requirements are met
Wherein, PwTo the power of the frequency point to be measured, PjTo preset a threshold value, Pz1For the first detection window power, Pz2For the second detection window power, Pz3Is the third detection window power, Pz4Is the fourth detection window power, k1Is a weighting parameter, k, corresponding to the first detection window2Is a weighting parameter, k, corresponding to the second detection window3Is a weighting parameter, k, corresponding to the third detection window4Weighting parameters corresponding to the fourth detection window;
s6, if yes, reserving the frequency point to be tested; and if not, filtering the frequency point to be detected.
2. The method of claim 1, further comprising:
respectively arranging a first window and a second window at the positions, which are positioned at the two sides of the frequency point to be detected in the speed dimension and have the same distance with the frequency point to be detected, in the echo signal frequency spectrum;
if the first window and the second window do not cover the echo signal corresponding to the stationary target, determining that the first window is the first detection window and determining that the second window is the second detection window;
and if the second window covers the echo signal corresponding to the static target, forming a second detection window in the second window in the area where the echo signal corresponding to the static target is removed, and reversely extending the first window relative to the second window to form the first detection window, wherein the total width of the first detection window and the second detection window is equal to the total width of the first window and the second window.
3. The method of claim 2, wherein the first window and the second window are equal in width in the velocity dimension and have 4 velocity gates and equal in width in the distance dimension and have 5-8 distance gates.
4. The method of claim 1, further comprising:
respectively arranging a third window and a fourth window at the positions, which are positioned at the two sides of the frequency point to be detected in the distance dimension and have the same distance with the frequency point to be detected, in the echo signal frequency spectrum;
if the third window and the fourth window do not cover the echo signals of all targets in the blind area, determining that the third window is the third detection window and determining that the fourth window is the fourth detection window;
if the fourth window covers the echo signals of all the targets in the blind area, the area where the echo signals of all the targets in the blind area are removed in the fourth window forms the fourth detection window, the third window is reversely extended relative to the fourth window to form the third detection window, and the total width of the third detection window and the fourth detection window is equal to the total width of the third window and the fourth window.
5. The method of claim 4, wherein the third window and the fourth window are equal in width in the velocity dimension and 3-6 velocity gates and equal in width in the distance dimension and 5 distance gates.
6. The method according to any one of claims 1-5, further comprising:
protection windows are respectively arranged on two sides of the frequency point to be detected in the speed dimension and the distance dimension of the echo signal frequency spectrum, the width of each protection window in the speed dimension is equal to the distance between the frequency point to be detected and the first detection window and the second detection window in the speed dimension, and the width is 1-2 speed threshold values; the width of each protection window in the distance dimension is equal to the distance between the frequency point to be detected and the third detection window and the fourth detection window in the distance dimension, and the width is 1-2 distance threshold values.
7. The method according to any one of claims 1-5, further comprising:
detecting whether the echo amplitude of the amplitude dimension of each frequency point in the echo signal frequency spectrum is smaller than a first preset power threshold value and reaches a second preset power threshold value;
if the echo amplitude reaches the first preset power threshold, determining that the frequency point belongs to the echo signal corresponding to the static target;
and if the echo amplitude is smaller than the second preset power threshold, determining that the frequency point belongs to the echo signal of each target in the blind area.
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Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112698293A (en) * | 2020-12-21 | 2021-04-23 | 广州极飞科技有限公司 | Radar signal processing method and device and aircraft |
| CN115656961A (en) * | 2022-12-26 | 2023-01-31 | 南京楚航科技有限公司 | OS-CFAR processing method and system based on parallel processor |
Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2078213A2 (en) * | 2006-11-02 | 2009-07-15 | Raytheon Canada Limited | A moving target detector for radar systems |
| JP2011169829A (en) * | 2010-02-19 | 2011-09-01 | Toshiba Corp | Meteorological radar signal processing apparatus and ground clutter removing method therefor |
| US20120293361A1 (en) * | 2011-05-17 | 2012-11-22 | Robert Stephen Mowbray | Radar clutter suppression system |
| US20130201054A1 (en) * | 2012-02-02 | 2013-08-08 | Raytheon Canada Limited | Knowledge Aided Detector |
| CN106342246B (en) * | 2011-06-14 | 2014-03-26 | 中国航空工业集团公司雷华电子技术研究所 | A kind of weather radar land clutter inhibition method |
| CN104199002A (en) * | 2014-09-12 | 2014-12-10 | 中国航空工业集团公司雷华电子技术研究所 | Radar information processing method used for restraining false-alarm objects of rotary blades of wind driven generators |
| US20160025849A1 (en) * | 2012-12-20 | 2016-01-28 | Raytheon Canada Limited | Methods and apparatus for 3d radar data from 2d primary surveillance radar and passive adjunct radar |
| US20160061944A1 (en) * | 2014-08-29 | 2016-03-03 | Furuno Electric Co., Ltd. | Clutter suppressing device and radar apparatus provided with the same |
| CN106249211A (en) * | 2016-08-05 | 2016-12-21 | 中国电子科技集团公司第二十八研究所 | A kind of sea clutter and sexual intercourse Clutter suppression algorithm |
| CN106569208A (en) * | 2016-11-15 | 2017-04-19 | 南京理工大学 | Clutter map-based airport runway foreign matter detection method |
| CN107121670A (en) * | 2017-04-12 | 2017-09-01 | 东南大学 | A kind of anti-unmanned plane system of defense based on synthetic aperture radar |
| CN107490789A (en) * | 2017-08-16 | 2017-12-19 | 成都纳雷科技有限公司 | Trailer-mounted radar signal target detection method and device based on CFAR detection |
-
2019
- 2019-12-30 CN CN201911399808.0A patent/CN111060880B/en active Active
Patent Citations (12)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2078213A2 (en) * | 2006-11-02 | 2009-07-15 | Raytheon Canada Limited | A moving target detector for radar systems |
| JP2011169829A (en) * | 2010-02-19 | 2011-09-01 | Toshiba Corp | Meteorological radar signal processing apparatus and ground clutter removing method therefor |
| US20120293361A1 (en) * | 2011-05-17 | 2012-11-22 | Robert Stephen Mowbray | Radar clutter suppression system |
| CN106342246B (en) * | 2011-06-14 | 2014-03-26 | 中国航空工业集团公司雷华电子技术研究所 | A kind of weather radar land clutter inhibition method |
| US20130201054A1 (en) * | 2012-02-02 | 2013-08-08 | Raytheon Canada Limited | Knowledge Aided Detector |
| US20160025849A1 (en) * | 2012-12-20 | 2016-01-28 | Raytheon Canada Limited | Methods and apparatus for 3d radar data from 2d primary surveillance radar and passive adjunct radar |
| US20160061944A1 (en) * | 2014-08-29 | 2016-03-03 | Furuno Electric Co., Ltd. | Clutter suppressing device and radar apparatus provided with the same |
| CN104199002A (en) * | 2014-09-12 | 2014-12-10 | 中国航空工业集团公司雷华电子技术研究所 | Radar information processing method used for restraining false-alarm objects of rotary blades of wind driven generators |
| CN106249211A (en) * | 2016-08-05 | 2016-12-21 | 中国电子科技集团公司第二十八研究所 | A kind of sea clutter and sexual intercourse Clutter suppression algorithm |
| CN106569208A (en) * | 2016-11-15 | 2017-04-19 | 南京理工大学 | Clutter map-based airport runway foreign matter detection method |
| CN107121670A (en) * | 2017-04-12 | 2017-09-01 | 东南大学 | A kind of anti-unmanned plane system of defense based on synthetic aperture radar |
| CN107490789A (en) * | 2017-08-16 | 2017-12-19 | 成都纳雷科技有限公司 | Trailer-mounted radar signal target detection method and device based on CFAR detection |
Non-Patent Citations (5)
| Title |
|---|
| DING TAO: ""A Segmentation-Based CFAR Detection Algorithm Using Truncated Statistics"", 《 IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING》 * |
| 姚远飞 等: ""降低船用连续波雷达虚警概率的海杂波抑制方法"", 《电讯技术》 * |
| 王博: ""气象雷达抑制机场宽带杂波方法研究"", 《现代雷达》 * |
| 翟海涛 等: ""基于视频信号的自适应云雨杂波抑制技术"", 《指挥信息系统与技术》 * |
| 高雁: ""步进频率高分辨雷达目标恒虚警检测技术研究"", 《中国优秀硕士学位论文全文数据库 信息科技辑》 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN112698293A (en) * | 2020-12-21 | 2021-04-23 | 广州极飞科技有限公司 | Radar signal processing method and device and aircraft |
| CN115656961A (en) * | 2022-12-26 | 2023-01-31 | 南京楚航科技有限公司 | OS-CFAR processing method and system based on parallel processor |
| CN115656961B (en) * | 2022-12-26 | 2023-03-10 | 南京楚航科技有限公司 | OS-CFAR processing method and system based on parallel processor |
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