CN111896928B - Multi-station radar target detection method based on active deception interference elimination - Google Patents

Multi-station radar target detection method based on active deception interference elimination Download PDF

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CN111896928B
CN111896928B CN202010793493.4A CN202010793493A CN111896928B CN 111896928 B CN111896928 B CN 111896928B CN 202010793493 A CN202010793493 A CN 202010793493A CN 111896928 B CN111896928 B CN 111896928B
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radar
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interference
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CN111896928A (en
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周宇
张诗羽
马忠晗
张林让
李亚超
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Xidian University
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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
    • G01S7/023—Interference mitigation, e.g. reducing or avoiding non-intentional interference with other HF-transmitters, base station transmitters for mobile communication or other radar systems, e.g. using electro-magnetic interference [EMI] reduction techniques
    • 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
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/414—Discriminating targets with respect to background clutter
    • 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
    • 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
    • G01S7/41—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00 using analysis of echo signal for target characterisation; Target signature; Target cross-section
    • G01S7/418—Theoretical aspects
    • Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
    • Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
    • Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
    • Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
    • Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation

Abstract

The invention discloses a multi-station radar target detection method based on active deception interference cancellation, which designs an interference cancellation algorithm on the basis of traditional centralized detection and can perform active deception interference suppression under the condition of ensuring target detection performance. The method comprises the following specific steps: 1. constructing a multi-station radar system, 2, receiving signals and transmitting the signals into a fusion center, 3, carrying out spatial registration on the signals, 4, obtaining deception interference test statistics, 5, judging whether a unit contains interference signals, if yes, executing the step 4, otherwise executing the steps 5 and 6, executing the steps 8 and 7 after constructing interference elimination test statistics, executing the steps 8 and 8 after constructing centralized test statistics, judging whether a space unit has a target, 9, judging whether the space unit has an undetected unit, if yes, executing the step 3, otherwise executing the steps 10 and 10, and ending the detection.

Description

Multi-station radar target detection method based on active deception interference elimination
Technical Field
The invention belongs to the technical field of radio orientation, and further relates to a multi-station radar target detection method based on active spoofing interference elimination in the technical field of multi-station radars. The method can be used for radar target detection of the multi-station radar in the deception jamming environment, and can inhibit active deception jamming while detecting targets.
Background
Multi-station radar cooperative target detection is an important trend in future development of radar equipment. Compared with a single-base radar, the multi-station radar has great potential and advantages in the aspects of target detection, anti-electronic reconnaissance, anti-interference capability and the like, and is mainly characterized in that the multi-station radar can effectively find weak targets, even invisible targets coated with wave absorbing materials by utilizing space diversity gain. However, in the detection environment where the spoofing interference exists, the multi-station radar detection detects the spoofing interference signal emitted by the jammer as a target detection, so that the false alarm rate of the spoofing interference signal is increased, and the data processing load after detection is increased.
The Western A electronics technology university discloses a multi-station radar signal level fusion target detection method based on signal-to-noise ratio information in a patent document (application number 201910518176.9, application publication number: CN 110161479A) applied by the Western A electronics technology university. The method comprises the steps of firstly selecting a unit to be detected, determining local observation data of each radar of the unit, then calculating local statistics by utilizing the local observation data, calculating a weighted value of each statistic based on signal to noise ratio information, finally calculating global statistics by weighting and summing all local statistics, comparing the global statistics with a preset threshold, and judging that a target exists if the global statistics are higher than the threshold. The invention improves the detection probability of the multi-station radar system to the target. However, the method still has the disadvantage that in engineering practice, the target neighboring units collect part of target observation data, and the detection statistics of the target neighboring units are calculated to be higher than the pure noise statistics by using a weighted summation mode, so that the target neighboring units have higher false alarm rates. If the deception jamming exists in the detection environment, a large number of units in the common view area contain deception jamming, and when the method is adopted for target detection, the false alarm rate of more units without targets can be increased.
Yang Yang, su Hongtao, etc. in their published papers "Spatial resolution cell based centralized target detection in multistatic radar" (Signal Processing 152 (2018) 238-246) propose a centralized multi-station radar target detection method based on a spatial resolution unit. The method comprises the steps of firstly calculating and detecting the global statistic by using a local signal by using a spatial registration technology, then comparing the global statistic with a threshold to detect a unit higher than the threshold, and finally searching the peak value in all units higher than the threshold to find the maximum value as a target to detect the maximum value. The method has the defects that the unit with the largest total quantity in the common view area is taken as the unit where the target is located, and when the detection is carried out in a deceptive interference environment, deceptive interference with larger power than the target is taken as true detection, so that the true target is missed to be detected and false targets are generated.
In summary, for the application of the multi-station radar target detection method in the existing radio direction, the existing method cannot eliminate the false target generated by the deceptive interference, which causes the problems of increased post-processing load including true and false target identification and data processing and the like and reduced multi-station radar detection performance.
Disclosure of Invention
The invention aims to solve the problem of reduced multi-station radar detection performance in a deception jamming environment, and reduce false targets under the condition that the detection probability of targets is not reduced compared with the traditional method.
The specific idea for realizing the aim of the invention is as follows: the method comprises the steps of improving the existing multi-station radar detection method, firstly selecting 1 space unit to be detected, judging whether the selected space unit contains deception interference, constructing interference elimination detection statistics for the detection unit containing deception interference to eliminate the influence of deception interference on detection performance, then carrying out target detection, constructing direct detection statistics for the space units which do not contain the interference, and then carrying out target detection.
The specific steps for realizing the aim of the invention comprise the following steps:
(1) Constructing a multi-station radar system:
(1a) Deploying a multi-station radar system comprising 1 signal fusion detection center, M radar receiving stations and 1 radar transmitting station;
(1b) Dividing the common view area irradiated by each radar receiving station beam into a plurality of space units;
(2) Receiving radar echo signals and sampling:
sampling echo signals of all radar receiving stations, and transmitting the obtained signal vectors into a fusion center;
(3) Selecting one undetected space unit from the common view area, and calculating the observation vector of the selected unit;
(4) Obtaining spoofing interference test statistics:
taking the square sum of the maximum two elements in the observation vector of the selected space unit as a deception jamming test statistic;
(5) Judging whether the test statistic is greater than a test threshold, if so, considering that the selected space unit contains deceptive interference, and executing the step (6); otherwise, the selected space unit is considered to not contain deception jamming, and step (7) is executed;
(6) Calculating interference cancellation detection statistics:
taking the sum of squares of all elements except the maximum two elements in the observation vector of the selected space unit as detection statistics, and executing the step (8);
(7) Calculating detection statistics:
taking the sum of squares of all elements in the observation vector of the selected space unit as detection statistics, and executing the step (8);
(8) Determining the selected spatial units with detection statistics greater than a detection threshold as spatial units containing targets;
(9) Judging whether all detection space units in the common view area are selected, if yes, executing the step (3), otherwise, executing the step (10);
(10) And ending the detection.
Compared with the prior art, the invention has the following advantages:
firstly, the invention takes the square sum of all elements except the maximum two elements in the selected space unit observation vector as detection statistics, and solves the problem that the false alarm rate of the target or the adjacent unit of deception interference is too high when the target is detected in the deception interference environment, so that the false alarm rate is reduced when the target is detected in the active deception environment, and the detection accuracy is improved.
Secondly, the invention calculates interference elimination detection statistics for all space units containing deception interference in the common vision area and detects the space units, thereby solving the problems of true target omission and false target generation in deception interference environment in the prior art, and reducing the generation of false targets on the premise of ensuring the target detection performance.
Drawings
FIG. 1 is a flow chart of the present invention;
FIG. 2 is a graph showing a comparison of single detection results of a simulation experiment of the present invention;
FIG. 3 is a graph of target detection probability versus simulation experiment of the present invention;
fig. 4 is a graph of the probability of rejection of spoofing versus the simulation of the present invention.
Detailed Description
The following describes the embodiments of the present invention in further detail with reference to the accompanying drawings.
The specific steps of the present invention will be described in further detail with reference to fig. 1.
And 1, constructing a multi-station radar system.
A multi-station radar system is deployed, and comprises a signal fusion detection center, M radar receiving stations and 1 radar transmitting station. Wherein, the coordinates of the radar receiving station part are as follows
Figure BDA0002624607500000031
m=1, 2, 3..m, m.gtoreq.3, coordinates of radar transmitting station are +.>
Figure BDA0002624607500000041
Is a position of (c).
And dividing radar common view areas into G space units in a radar fusion center, wherein G is more than or equal to 1. The multi-station radar space resolution unit is generally complex in shape, the square unit is adopted in the invention, and the square unit size meets the following formula:
Figure BDA0002624607500000042
Figure BDA0002624607500000043
wherein L is x 、L x Representing the length and width of each unit, taking the minimum value of min (DEG) for operation, and delta r m Represents the range resolution, g, of the mth radar receiving station m The subscript representing the furthest element from radar m.
And step 2, sampling the received signals and transmitting the sampled signals into a fusion center.
The radar echo signal is received, when an active deception jamming environment exists in the detection environment, the echo signal is composed of a target echo signal, a deception jamming signal forwarded by an jammer and internal noise, and the method can be specifically expressed as:
Figure BDA0002624607500000044
wherein r is m (t) represents a reception signal of an mth local radar reception station, e m,k (t) represents the kth target echo signal, k=1, 2,.. m,q (t) represents the qth interfering signal, q=1, 2,..q, q+.1, n m (t) represents the power sigma 2 Is a gaussian white noise of (c).
Sampling echo signals to obtain signal vectors
Figure BDA0002624607500000045
Wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure BDA0002624607500000046
representing a signal vector after sampling a signal received by an mth radar receiving station, T s Represents the sampling rate, N represents the length of the signal vector, n=round (T s PRT), round (·) represents the rounding operation, PRT represents the radar pulse repetition period. And sending the signal vector obtained by sampling to a fusion center.
And 3, performing spatial registration.
After the fusion center receives the signal vector of each radar, the signal vector is data collected under the reference coordinate system of each radar receiving station, and the signal vector is required to be converted into a unified space coordinate for target detection. From common viewIs selected as an undetected space unit
Figure BDA0002624607500000047
The selected observation vector is calculated according to the following equation:
Figure BDA0002624607500000048
Figure BDA0002624607500000051
wherein z is g Representing the observation vector of the g-th spatial unit,
Figure BDA0002624607500000052
representing the reference vector of the g-th spatial element for the 1 st radar receiving station,/for the radar receiving station>
Figure BDA0002624607500000053
Representing the reference vector of the g-th spatial element for the M-th radar receiving station, (. Cndot.) H Representing conjugate transpose operations, [] T Transpose operation s (·) represents the complex envelope of the signal transmitted by the radar transmitting station, < ->
Figure BDA0002624607500000054
Representing the corresponding time delay of the g-th spatial element relative to the radial distance of the mth radar receiving station.
Figure BDA0002624607500000055
c represents the speed of light.
And 4, obtaining the spoofing interference test statistic.
For the deceptive interference, since the real target does not exist in the position of the deceptive interference, signals of the deceptive interference are distributed in different space units after being converted into a unified coordinate system, energy is dispersed relatively to the target, and the observed vector of the space unit affected by the deceptive interference is usually derived from the deceptive interference at most two elements, and the two elements are generally far larger than other elements. Using this feature, test statistics can be designed to distinguish whether a spatial element contains rogue interference. Specifically, the spoofing interference test statistic may be calculated from the observed vector of the selected spatial cell according to the following equation:
Figure BDA0002624607500000056
wherein z is i,g ,z j,g Representing the largest two elements in the observation vector, i, j representing the subscripts of the largest two elements in the observation vector.
And 5, judging whether the space unit contains deception jamming or not.
The spoofing interference check threshold is calculated from the observation vector according to the following equation:
Figure BDA0002624607500000057
wherein, gamma represents the inspection threshold,
Figure BDA0002624607500000058
the chi-square distribution inverse cumulative function representing a degree of freedom of 4, κ representing the probability that the selected spatial cell is determined to contain spoofing without containing spoofing, a modulo operation, z m,g Representing the mth element in the g-th spatial unit observation vector.
Judging whether the test statistic is greater than a test threshold, if so, considering that the selected space unit contains deceptive interference, and executing the step 6; otherwise, the selected spatial unit is considered to contain no spoofing interference, step 7 is performed.
And 6, calculating interference elimination detection statistics.
The inclusion of spoofing in a spatial cell requires the construction of spoofing cancellation detection statistics to cancel the detection performance impact of the spoofing on the selected cell.
When the interference cancellation detection statistic is constructed as follows:
Figure BDA0002624607500000061
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure BDA0002624607500000062
a detection statistic vector representing the g-th spatial unit,>
Figure BDA0002624607500000063
power maximum likelihood estimation representing spoofing interference, < >>
Figure BDA0002624607500000064
The detection threshold is designed according to the Newman-Pearson criterion and can be calculated according to the following formula:
Figure BDA0002624607500000065
where eta is the threshold for the spoofing interference cancellation detection statistic,
Figure BDA0002624607500000066
the chi-square distribution inverse cumulative function with the degree of freedom of 2M-4 is represented, and alpha represents the false alarm rate.
And 7, calculating detection statistics.
The spatial units do not contain spoofing, and if the spoofing cancellation statistic is constructed, the detection performance of the selected spatial units is reduced, so the statistic is directly constructed according to the following formula:
Figure BDA0002624607500000067
and 8, judging whether the target exists in the selected space unit or not.
The statistic is compared to a threshold. The statistic is compared to a threshold. If it is
Figure BDA0002624607500000068
Determining that a target is present in the spatial cell; if->
Figure BDA0002624607500000069
Determining that there is no target in the space unit;
and 9, judging whether all detection space units in the common view area are selected, if yes, executing the step 3, otherwise, executing the step 10.
And step 10, ending the detection.
The effect of the invention can be further demonstrated by the following simulation experiment.
1. Simulation conditions:
the simulation experiment of the invention is that the computer is mainly configured as follows: CPU is Intel Core i7-7700, RAM is 8GB; the operating system is Windows 7; the running software is completed on Matlab R2017 b.
The constructed multi-station radar system comprises 1 transmitting station and 7 receiving stations, wherein the radar transmitting stations are positioned at (0, 0) km, the radar receiving stations are respectively positioned at (4.4, -30) km, (1.8, -20) km, (0.8, -10) km, (0, 0) km, (0.8,10) km, (1.8,20) km and (4.4,30) km. Three targets are set in the common monitored area, and the position coordinates of the targets are (35.3,2.2) km, (34.1,1.6) km and (33.5,1.2) km respectively. Consider a self-defense type forwarding jammer in the scene, the position coordinates of which are (35.3,2.2) km, 3 pulse signals are forwarded, and the forwarding delays are 6.67us, 13.3us and 3us respectively.
2. Simulation content and result analysis:
the simulation experiment of the invention has three.
The simulation experiment 1 is to perform one-time target detection simulation on rectangular common view areas with X-axis coordinate ranges of 32-39 km and Y-axis coordinate ranges of 1-3 km under the conditions that the signal-to-noise ratio of a received signal is 10dB and the dry noise ratio is 16dB by adopting the method and the existing centralized detection method based on the spatial resolution unit, so that target detection results of the two detection methods shown in fig. 2 are obtained.
The centralized detection method based on the spatial resolution unit is as follows: yang Yang, su Hongtao, etc. in their published papers "Spatial resolution cell based centralized target detection in multistatic radar" (Signal Processing 152 (2018) 238-246) propose a centralized multi-station radar target detection method based on a spatial resolution unit.
The abscissa in fig. 2 represents the X-axis coordinates of the space cell position in kilometers, and the ordinate represents the Y-axis coordinates of the space cell position in kilometers. The black part in fig. 2 represents an area constituted by space units without targets or decoys, the bright spots represent space units determined to be targets, the bright spots surrounded by circles represent space units where targets are located, and the bright spots surrounded by boxes represent space units where decoys generated by spoofing interference are located. FIG. 2 (a) shows the detection result of target detection by the conventional method; FIG. 2 (b) shows the detection result of the target detection according to the present invention.
As can be seen from fig. 2, when the target detection method is performed by using the centralized detection method based on the spatial resolution unit, there are bright spots on three target positions, namely (35.3,2.2) km, (34.1,1.6) km, (33.5,1.2) km, and a large number of bright spots on other positions. And the detection result of the invention shows that the three target positions have bright spots, and the other positions have no bright spots. Compared with a centralized detection method based on a spatial resolution unit for target detection, the method provided by the invention has the advantage that false targets are restrained from being generated.
The simulation experiment 2 is to simulate the target detection probability of a single target in different signal to noise ratios in the range of 0 to 18dB by adopting the method and the existing centralized detection method based on the spatial resolution unit, so as to obtain a target detection probability comparison graph of FIG. 3.
In fig. 3, the abscissa represents the signal-to-noise ratio, the unit is dB, the ordinate represents the target detection probability, the curve marked with an asterisk represents the target detection probability curve for performing target detection by using the centralized detection method based on the spatial resolution unit, and the curve marked with an inverted triangle represents the target detection probability curve for performing target detection by using the present invention.
The target detection probability is calculated by the following formula:
Figure BDA0002624607500000081
wherein P is d Representing the probability of detection of the target, n d Represents the number of times the target was detected in the experiment, C d The number of each signal-to-noise ratio experiment is represented, and the number of each signal-to-noise ratio experiment of the simulation experiment 2 is 1000.
As can be seen from fig. 3, the target detection probability curve of the target sample is substantially coincident with the target detection probability curve of the conventional detection method, which indicates that the detection performance of the present invention is not degraded compared with the detection performance of the conventional method.
The simulation experiment 3 is to simulate the deception target rejection probability of a single deception target unit containing deception interference but not containing a target space unit under different interference-to-noise ratios by adopting the method and the existing centralized detection method based on the space resolution unit, so as to obtain a deception interference rejection probability comparison graph of fig. 4.
The abscissa in fig. 4 is the dry-to-noise ratio, the unit is dB, the ordinate is the probability of spoofing interference rejection, the curve marked with an asterisk represents the probability of spoofing interference rejection curve detected by the centralized detection method based on the spatial resolution unit, and the curve marked with an inverted triangle represents the probability of spoofing interference rejection curve detected by the target detection method of the present invention.
The deception jamming rejection probability is calculated by the following formula:
Figure BDA0002624607500000082
wherein P is j Representing the probability of rejection of spoofing type, n j Representing the number of times in the experiment that a spatial unit containing spoofing but not containing a target is not determined to contain a target, C j The number of each dry-to-noise ratio experiment is represented, and the number of each dry-to-noise ratio experiment of the simulation experiment 3 is 1000.
As can be seen from fig. 4, when the interference-to-noise ratio of spoofing is less than 6dB, the rejection probability of the two methods basically coincides and is close to 1, the rejection probability curve of the prior method decreases with the increase of the interference-to-noise ratio, and when the interference-to-noise ratio is 14dB, the rejection probability reaches 0; the rejection probability curve with the invention reaches the lowest point of 0.85 when the dry noise ratio is 11dB, then the rejection probability is increased along with the increase of the dry noise ratio, and reaches 1 when the dry noise ratio reaches 15 dB. The method has the advantage that the deception jamming performance is greatly improved compared with the prior method.

Claims (7)

1. A multi-station radar target detection method based on active deception interference cancellation is characterized in that a multi-station radar system is composed of a radar transmitting station and a plurality of radar receiving stations, and binary hypothesis test is constructed to judge whether interference needs interference cancellation or not; constructing interference elimination detection statistics and calculating corresponding detection thresholds; the method comprises the following specific steps:
(1) Constructing a multi-station radar system:
(1a) Deploying a multi-station radar system comprising 1 signal fusion detection center, M radar receiving stations and 1 radar transmitting station;
(1b) Dividing the common view area irradiated by each radar receiving station beam into a plurality of space units;
(2) Receiving radar echo signals and sampling:
sampling echo signals of all radar receiving stations, and transmitting the obtained signal vectors into a fusion center;
(3) Selecting one undetected space unit from the common view area, and calculating the observation vector of the selected unit;
(4) Obtaining spoofing interference test statistics:
taking the square sum of the maximum two elements in the observation vector of the selected space unit as a deception jamming test statistic;
(5) Judging whether the test statistic is greater than a test threshold, if so, considering that the selected space unit contains deceptive interference, and executing the step (6); otherwise, the selected space unit is considered to not contain deception jamming, and step (7) is executed;
(6) Calculating interference cancellation detection statistics:
taking the sum of squares of all elements except the maximum two elements in the observation vector of the selected space unit as detection statistics, and executing the step (8);
(7) Calculating detection statistics:
taking the sum of squares of all elements in the observation vector of the selected space unit as detection statistics, and executing the step (8);
(8) Determining the selected spatial units with detection statistics greater than a detection threshold as spatial units containing targets;
(9) Judging whether all detection space units in the common view area are selected, if yes, executing the step (3), otherwise, executing the step (10);
(10) And ending the detection.
2. The active spoofing interference cancellation based multi-station radar target detection method of claim 1 wherein: the sampled signal vector described in step (2) is determined by:
Figure FDA0002624607490000021
Figure FDA0002624607490000022
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure FDA0002624607490000023
representing the signal vector after sampling the signal received by the 1 st radar receiving station, r 1 (. 1 st radar receiving station receives analog signal, T s Represents the sampling rate, N represents the length of the signal vector, n=round (T s PRT), round (·) represents the rounding operation, PRT represents the radar pulse repetition period, +.>
Figure FDA0002624607490000024
Representing signal vector after receiving signal sampling of Mth radar receiving station, r M (. Cndot.) represents the analog signal received by the mth radar receiving station.
3. The active spoofing interference cancellation based multi-station radar target detection method of claim 2 wherein: the observation vector in step (3) is determined by the following formula:
Figure FDA0002624607490000025
Figure FDA0002624607490000026
wherein z is g Representing the observation vector of the g-th spatial unit,
Figure FDA0002624607490000027
representing the reference vector of the g-th spatial element for the 1 st radar receiving station,/for the radar receiving station>
Figure FDA0002624607490000028
Representing the reference vector of the g-th spatial element for the M-th radar receiving station, (. Cndot.) H Representing conjugate transpose operations, [] T Transpose operation s (·) represents the complex envelope of the signal transmitted by the radar transmitting station, < ->
Figure FDA0002624607490000029
Representing the corresponding time delay of the g-th spatial element relative to the radial distance of the mth radar receiving station.
4. The active spoofing interference cancellation based multi-station radar target detection method of claim 3 wherein: the test threshold in step (5) is determined by the following equation:
Figure FDA00026246074900000210
wherein, gamma represents the inspection threshold,
Figure FDA00026246074900000211
the chi-square distribution inverse cumulative function representing a degree of freedom of 4, κ representing the probability that the selected spatial cell was determined to contain spoofing without spoofing, |·| representing a modulo operation, z m,g Representing the mth element in the observation vector of the g-th space unit, and i, j represent the subscripts of the largest two elements in the observation vector.
5. The active spoofing interference cancellation based multi-station radar target detection method of claim 1 wherein: the detection threshold in step (6) is determined by the following formula:
Figure FDA0002624607490000031
wherein sigma 2 Representing the noise power level inside the receiver,
Figure FDA0002624607490000032
the chi-square distribution inverse cumulative function with the degree of freedom of 2M-4 is represented, and alpha represents the false alarm rate.
6. The active spoofing interference cancellation based multi-station radar target detection method of claim 1 wherein: the detection threshold in step (7) is determined by the following formula:
Figure FDA0002624607490000033
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure FDA0002624607490000034
representing the degree of freedom as 4 chi-square distributionAn inverse cumulative function.
7. The active spoofing interference cancellation based multi-station radar target detection method of claim 3 wherein: the time delay in step (3) is determined by the following equation:
Figure FDA0002624607490000035
wherein, the liquid crystal display device comprises a liquid crystal display device,
Figure FDA0002624607490000036
x represents the abscissa of the position of the g-th space unit t An abscissa indicating the location of the radar transmitting station, < >>
Figure FDA0002624607490000037
Representing the ordinate, y, of the position of the g-th spatial unit t Ordinate indicating the position of the radar transmitting station, < >>
Figure FDA0002624607490000038
The abscissa indicating the position of the mth radar receiving station, m=1, 2,..>
Figure FDA0002624607490000039
The ordinate indicating the position of the mth radar receiving station, and c indicating the speed of light.
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