CN109143184B - Double-threshold detection method for scanning radar - Google Patents
Double-threshold detection method for scanning radar Download PDFInfo
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- CN109143184B CN109143184B CN201811266214.8A CN201811266214A CN109143184B CN 109143184 B CN109143184 B CN 109143184B CN 201811266214 A CN201811266214 A CN 201811266214A CN 109143184 B CN109143184 B CN 109143184B
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/36—Means for anti-jamming, e.g. ECCM, i.e. electronic counter-counter measures
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- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/28—Details of pulse systems
- G01S7/285—Receivers
- G01S7/292—Extracting wanted echo-signals
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Abstract
The invention relates to a double-threshold detection method for a scanning radar, and belongs to the technical field of radar target detection. The method comprises the following steps: step 1, receiving radar echoes for more than 3 times; step 2, performing down-conversion, pulse pressure and MTD processing on the current radar echo, and then performing modeling to obtain a frequency domain echo; step 3, judging whether the data in the current frequency domain echo is higher than a second threshold, and if so, jumping to step 6; otherwise, skipping step 4; step 4, finding out a target point which is higher than a first threshold in the current frequency domain echo; step 5, carrying out target point trace correlation on the target point between the current frequency domain echo thresholds and the previous two frequency domain echoes within a certain threshold range of speed, distance and direction; step 6, recording the distance, the speed and the direction of the detected target; step 7, removing the detected target from the frequency domain echo to obtain a noise frequency spectrum; and 8, subtracting the noise spectrum from the frequency domain echo to obtain a target point trace after double-threshold detection. The method can reduce the noise floor and effectively improve the detection probability of the target.
Description
Technical Field
The invention relates to a double-threshold detection method for a scanning radar, and belongs to the technical field of radar target detection.
Background
When radar detects the target, owing to receive complicated external environment influence, the target is often polluted by noise and clutter, is under the noise basement to lead to not detecting out, promptly: the probability of missed detection is high. In an environment with prominent noise and clutter characteristics, the conventional method for suppressing noise and clutter, such as the CFAR method, is not ideal in detecting a target. That is to say: it often occurs that small objects exist below the noise floor, resulting in small objects not being detected or noise being detected as small objects.
Through simulation and actual measurement, the following results are found: the noise is very much like a small object after passing through the pulse pressure and MTD. For the case that a small target exists under the noise floor, the CFAR algorithm in the conventional data processing of the radar cannot detect the small target. When the noise threshold is reduced, although more detected 'targets' exist, unreal targets appear, namely 'false targets' increase, and therefore the probability of missed detection is improved. Therefore, how to further improve the detection probability of the scanning radar on the small target below the noise floor and suppress the noise is the target of the present application.
The method is based on the background of the scanning radar, noise, clutter and small targets submerged under a noise substrate are distinguished and detected by adopting a method with double thresholds and scanning point trace correlation as a main part, and the noise and clutter suppression capability and target detection performance of the scanning radar are improved.
Disclosure of Invention
The invention aims to provide a double-threshold detection method of a scanning radar, aiming at the technical defects that the missed detection rate is increased and the target detection capability is reduced because a target is covered under a noise substrate in a complex environment with noise and clutter as the main parts.
A double-threshold detection method for scanning radar comprises the following steps:
step one, receiving radar echo data scanned by a radar for multiple times;
step two, performing down-conversion, pulse pressure and MTD processing on the radar echo data of all X-time scanning received in the step one, and then performing modular calculation to obtain frequency domain echoes of all X-time scanning;
wherein X is greater than 2;
step three, judging whether the data in the frequency domain echo of the Xth scanning is higher than a second threshold, and jumping to the step seven if the data in the frequency domain echo of the Xth scanning is higher than the second threshold; otherwise, executing the step four;
wherein the second threshold is a high threshold;
finding out a target point with the assignment higher than a first threshold in the frequency domain echo of the Xth scanning;
wherein the first threshold is a low threshold;
step five, carrying out trace point correlation on the target point between the frequency domain echo thresholds of the Xth scanning and the targets of the frequency domain echo of the Xth scanning within a certain threshold range of speed, distance and direction at the X-1 st time;
step six, judging whether the X-th scanning target points in the step five are processed completely, if so, jumping to the step seven, otherwise, jumping to the step five;
step seven, confirming the targets detected in the step three and the step five as real targets, and recording the distance, the speed and the direction of the detected real targets;
step eight, removing the detected real target from the frequency domain echo of the Xth scanning to obtain a noise frequency spectrum;
and step nine, subtracting the noise frequency spectrum from the frequency domain echoes of all the X-time scanning to obtain a target trace after double-threshold detection.
Advantageous effects
Compared with the existing double-threshold detection algorithm, the double-threshold detection method of the scanning radar has the following beneficial effects:
1. the absolute threshold of the traditional double-threshold detection algorithm is fixed and is set to be a plurality of times of the mean value of noise, but the low threshold of the double-threshold detection algorithm is lower than that of the traditional algorithm, the effective detection of the target can be realized, and the detection rate meets the requirement;
2. the high threshold of the traditional double-threshold detection algorithm is dynamic, the high threshold of the double-threshold detection algorithm can be the same as or lower than that of the traditional double-threshold detection algorithm, and a target point detected in the threshold is subjected to point trace correlation and detection, so that noise and clutter are further removed, and a real target is screened;
3. the method of the invention can detect the small signal submerged in the noise while reducing the threshold, reduce the probability of missed detection and effectively improve the detection rate of the target.
Drawings
Fig. 1 is a flowchart of an implementation of a dual-threshold detection method for scanning radar according to the present invention.
Detailed description of the preferred embodiments
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer, 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 some embodiments of the present invention, but not all embodiments. All other embodiments, which can be obtained by a person skilled in the art without any inventive step based on the embodiments of the present invention, belong to the scope of the present invention.
Example 1
This embodiment illustrates a specific implementation of the method of the present invention, and as shown in fig. 1, is an implementation flow of an implementation flow chart of a double-threshold detection method for scanning radar according to the present invention.
A double-threshold detection method for scanning radar comprises the following steps:
step A, caching radar echo data of 3 times of radar scanning;
b, performing down-conversion, pulse pressure and MTD processing on the radar echo data of the 3-time scanning received in the step A, and then performing modulo calculation to obtain an echo frequency spectrum of the 3-time scanning;
step C, judging whether the data in the echo spectrum of the 3 rd scanning is higher than a second threshold, and jumping to the step G if the data is higher than the second threshold; otherwise, executing step D;
wherein, the second threshold is a high threshold, and is more than or equal to the relative threshold of the traditional CFAR algorithm in specific implementation;
d, judging whether the data in the echo frequency spectrum of the current scanning is higher than a target point of a first threshold or not, and analyzing a target point trace of the current scanning;
wherein, the first threshold is a low threshold which is lower than the absolute threshold of the traditional CFAR algorithm; in the specific implementation, the lower power is at least 2 dB;
e, judging whether the speed, the distance and the direction of the echo frequency spectrum and corresponding target points of the echo frequency spectrums of the 2 nd scanning and the 1 st scanning are within a certain threshold value, and if not, jumping to the step E; otherwise, executing step G;
in specific implementation, the threshold of the distance range is: the distance between the left door and the right door is 2 to 10; the threshold value of the speed range is determined by taking the target acceleration range into consideration, multiplying the speed change of single scanning obtained by the scanning period, and adding or subtracting 2-10 meters per second; the threshold range of the azimuth is between plus or minus 1 degree and 5 degrees;
step F, judging whether the data in the echo frequency spectrum of the current scanning is processed or not, and jumping to step G if the data in the echo frequency spectrum of the current scanning is processed; otherwise, jumping to the step E;
step G, regarding the currently detected target as a real target, and solving the distance, the speed and the direction of the real target to obtain the trace point of the real target;
step H, removing information corresponding to the real target detected in the step G from the echo spectrum to obtain a noise spectrum;
and step I, subtracting the noise spectrum generated in the step H from the echo spectrum output in the step B to obtain a target trace after double-threshold detection.
Experiments were performed using the described method. The test is performed on a certain type of vehicle based on the echoes of the scanning radar. I.e., three consecutive echoes, as input to step a and step B of the embodiment, table 1 below shows the effect of detecting the target in the embodiment.
In specific implementation, the measured data does not contain the noise of the target, so the target trace output in step I should be 0 theoretically. The detection probability is actually tested in a laboratory in a low-noise environment and is as high as 99%.
Further, the method of the invention is used for carrying out the car running experiment in a certain field of outsides in Shaanxi province, and the car runs for 4 times aiming at a certain car target, the test distance range of each experiment is more than ten kilometers, and the car runs for about 3 minutes.
Table 1 lists the measured data values of the probability of detecting a moving vehicle target by a radar in 4 experiments in the environment of external noise and clutter.
TABLE 1 probability comparison of double-threshold detection method with conventional CFAR detection target
The conventional target detection method in table 1 is the CFAR algorithm. Through statistics, compared with a conventional target detection algorithm, the false detection probability of the 1 st experiment is reduced from 16.25% to 3.12%, and is reduced by 13.13%; the false detection probability of the 2 nd experiment is reduced from 9.09% to 4.55%, and is reduced by 4.54%; the false detection probability of the 3 rd experiment is reduced from 9.52% to 2.38%, and is reduced by 7.14%; the false detection probability of the 4 th experiment is reduced from 10.6% to 4.26%, and is reduced by 6.34%; the average false detection probability of 4 experiments was reduced by 7.8%.
In summary, compared with the prior art, the detection probability can be improved from 80% to 90% under the same threshold condition. On the basis of ensuring 85% detection probability, the requirement of input SNR can be reduced by at least 2dB, so that high transmitting power is not needed, the power requirement on a radio frequency module is reduced, the hard cost of the scanning radar is reduced 1/3, and the technical advantage and the performance improvement have great significance.
While the foregoing is directed to the preferred embodiment of the present invention, it is not intended that the invention be limited to the embodiment and the drawings disclosed herein. Equivalents and modifications may be made without departing from the spirit of the disclosure, which is to be considered as within the scope of the invention.
Claims (4)
1. A double-threshold detection method for scanning radar is characterized in that: the method comprises the following steps:
step one, receiving radar echo data scanned by a radar for multiple times;
step two, performing down-conversion, pulse pressure and MTD processing on the radar echo data of all X-time scanning received in the step one, and then performing modular calculation to obtain frequency domain echoes of all X-time scanning;
step three, judging whether the data in the frequency domain echo of the Xth scanning is higher than a second threshold, and jumping to the step seven if the data in the frequency domain echo of the Xth scanning is higher than the second threshold; otherwise, executing the step four;
finding out a target point with the assignment higher than a first threshold in the frequency domain echo of the Xth scanning;
step five, carrying out trace point correlation on the target point between the frequency domain echo thresholds of the Xth scanning and the targets of the frequency domain echo of the Xth scanning within a certain threshold range of speed, distance and direction at the X-1 st time;
step six, judging whether the X-th scanning target points in the step five are processed completely, if so, jumping to the step seven, otherwise, jumping to the step five;
step seven, confirming the targets detected in the step three and the step five as real targets, and recording the distance, the speed and the direction of the detected real targets;
step eight, removing the detected real target from the frequency domain echo of the Xth scanning to obtain a noise frequency spectrum;
and step nine, subtracting the noise frequency spectrum from the frequency domain echoes of all the X-time scanning to obtain a target trace after double-threshold detection.
2. The double-threshold detection method for scanning radar according to claim 1, wherein: and in the second step, X is more than 2.
3. The dual-threshold detection method for scanning radar as claimed in claim 1, wherein: in step three, the second threshold is a high threshold.
4. The dual-threshold detection method for scanning radar as claimed in claim 1, wherein: in step four, the first threshold is the low threshold.
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| CN110187318B (en) * | 2019-04-23 | 2021-07-06 | 四川九洲防控科技有限责任公司 | Radar data processing method |
| CN110907929B (en) * | 2019-11-29 | 2022-12-09 | 成都纳雷科技有限公司 | Vehicle-mounted radar target detection method and device based on double-threshold detection |
| CN112485783B (en) * | 2020-09-29 | 2024-05-10 | 北京清瑞维航技术发展有限公司 | Object detection method, device, computer equipment and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102854496A (en) * | 2012-09-19 | 2013-01-02 | 中国民航大学 | Airborne meteorological radar ground clutter suppression method based on double threshold control |
| CN104931939A (en) * | 2015-06-03 | 2015-09-23 | 河海大学 | Missile-borne forwarding type interference inhibition method based on false target characteristics |
| CN105044686A (en) * | 2015-08-03 | 2015-11-11 | 中国电子科技集团公司第二十八研究所 | Radar dense false target interference inhibition method |
| CN105204017A (en) * | 2015-09-01 | 2015-12-30 | 北京理工大学 | High-resolution radar angle tracking method based on regularization optimization |
| CN106093904A (en) * | 2016-06-17 | 2016-11-09 | 电子科技大学 | Clutter map CFAR Methods based on multiframe double threshold hierarchical detection mechanism |
Family Cites Families (17)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| IT1170587B (en) * | 1983-12-13 | 1987-06-03 | Selenia Ind Elettroniche | ADAPTIVE PROCESSOR OF RADAR SIGNALS FOR THE DETECTION OF THE ECO AND THE CANCELLATION OF THE CLUTTER |
| US4796030A (en) * | 1987-02-20 | 1989-01-03 | Eaton Corporation | Dual threshold amplitude detector |
| JPWO2006123499A1 (en) * | 2005-05-16 | 2008-12-25 | 株式会社村田製作所 | Radar |
| CN100507601C (en) * | 2007-01-08 | 2009-07-01 | 清华大学 | Double-threshold constant false alurm motion target detecting method of double base synthetic aperture radar |
| CN106342244B (en) * | 2009-03-16 | 2012-10-31 | 中国航空工业集团公司雷华电子技术研究所 | Radar Weak target detecting method |
| JP5666987B2 (en) * | 2011-05-25 | 2015-02-12 | 株式会社デンソー | Moving object detection device |
| CN102662161B (en) * | 2012-05-24 | 2014-03-26 | 北京理工大学 | Channel monitoring mechanism based system and channel monitoring mechanism based method for suppressing multi-automobile anti-collision radar conflict |
| DE102012024999A1 (en) * | 2012-12-19 | 2014-06-26 | Valeo Schalter Und Sensoren Gmbh | Method for setting a detection threshold for a received signal of a frequency modulation continuous wave radar sensor of a motor vehicle depending on the noise level, radar sensor and motor vehicle |
| CN103257346B (en) * | 2013-05-15 | 2014-12-10 | 桂林电子科技大学 | Automotive anti-collision radar multi-target detecting method and system |
| CN103412291B (en) * | 2013-08-16 | 2015-02-04 | 四川九洲空管科技有限责任公司 | Secondary-radar-based achieving method of target multipath effect suppression technology |
| CN103439697B (en) * | 2013-08-23 | 2015-05-27 | 西安电子科技大学 | Target detection method based on dynamic programming |
| CN104330780B (en) * | 2014-09-25 | 2016-06-22 | 中国地质大学（武汉） | A kind of object detection method based on adaptive frequency domain no-coherence cumulating and device |
| CN104914422A (en) * | 2015-06-25 | 2015-09-16 | 中国船舶重工集团公司第七二四研究所 | Adaptive TBD radar weak target detection method |
| CN106842164B (en) * | 2017-03-14 | 2019-06-14 | 中国人民解放军国防科学技术大学 | Non- cooperation pulse compression radar Weak target detecting method based on Wavelet Denoising Method |
| CN107153178B (en) * | 2017-05-18 | 2020-04-10 | 西安电子科技大学 | Target detection method for external radiation source radar reference signal with multipath interference |
| CN107861107B (en) * | 2017-10-23 | 2021-02-05 | 电子科技大学 | Double-threshold CFAR (computational fluid dynamics) and trace point agglomeration method suitable for continuous wave radar |
| CN108414991B (en) * | 2018-02-08 | 2020-08-11 | 北京理工大学 | High-resolution radar non-uniform clutter scene micro-target constant false alarm detection method |
-
2018
- 2018-10-29 CN CN201811266214.8A patent/CN109143184B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102854496A (en) * | 2012-09-19 | 2013-01-02 | 中国民航大学 | Airborne meteorological radar ground clutter suppression method based on double threshold control |
| CN104931939A (en) * | 2015-06-03 | 2015-09-23 | 河海大学 | Missile-borne forwarding type interference inhibition method based on false target characteristics |
| CN105044686A (en) * | 2015-08-03 | 2015-11-11 | 中国电子科技集团公司第二十八研究所 | Radar dense false target interference inhibition method |
| CN105204017A (en) * | 2015-09-01 | 2015-12-30 | 北京理工大学 | High-resolution radar angle tracking method based on regularization optimization |
| CN106093904A (en) * | 2016-06-17 | 2016-11-09 | 电子科技大学 | Clutter map CFAR Methods based on multiframe double threshold hierarchical detection mechanism |
Non-Patent Citations (1)
| Title |
|---|
| Jiaqiu Ai ; Xuezhi Yang ; Jitao Song ; Zhangyu Dong ; Lu Jia ; Fang Zhou.Select All on Page.《 IEEE Journal of Oceanic Engineering》.2017,第267-279页. * |
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