CN113960536B - Multi-station radar multi-target detection method based on interference elimination - Google Patents
Multi-station radar multi-target detection method based on interference elimination Download PDFInfo
- Publication number
- CN113960536B CN113960536B CN202111231826.5A CN202111231826A CN113960536B CN 113960536 B CN113960536 B CN 113960536B CN 202111231826 A CN202111231826 A CN 202111231826A CN 113960536 B CN113960536 B CN 113960536B
- Authority
- CN
- China
- Prior art keywords
- interference
- radar
- station
- resolution unit
- spatial resolution
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Active
Links
- 238000001514 detection method Methods 0.000 title claims abstract description 70
- 230000008030 elimination Effects 0.000 title claims abstract description 7
- 238000003379 elimination reaction Methods 0.000 title claims abstract description 7
- 230000004927 fusion Effects 0.000 claims abstract description 45
- 239000011159 matrix material Substances 0.000 claims abstract description 33
- 238000012360 testing method Methods 0.000 claims abstract description 33
- 238000000034 method Methods 0.000 claims abstract description 16
- 238000012937 correction Methods 0.000 claims abstract description 5
- 239000013598 vector Substances 0.000 claims description 27
- 238000004364 calculation method Methods 0.000 claims description 5
- 238000003657 Likelihood-ratio test Methods 0.000 claims description 3
- 238000007476 Maximum Likelihood Methods 0.000 claims description 3
- 230000005540 biological transmission Effects 0.000 claims description 3
- 238000005070 sampling Methods 0.000 claims description 3
- 230000017105 transposition Effects 0.000 claims description 3
- 239000000654 additive Substances 0.000 claims description 2
- 230000000996 additive effect Effects 0.000 claims description 2
- 238000004088 simulation Methods 0.000 description 8
- 238000002474 experimental method Methods 0.000 description 3
- 238000012545 processing Methods 0.000 description 3
- 238000009825 accumulation Methods 0.000 description 1
- 238000004458 analytical method Methods 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000007499 fusion processing Methods 0.000 description 1
- 230000002195 synergetic effect Effects 0.000 description 1
- 230000008685 targeting Effects 0.000 description 1
Classifications
-
- 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
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/66—Radar-tracking systems; Analogous systems
- G01S13/72—Radar-tracking systems; Analogous systems for two-dimensional tracking, e.g. combination of angle and range tracking, track-while-scan radar
- G01S13/723—Radar-tracking systems; Analogous systems for two-dimensional tracking, e.g. combination of angle and range tracking, track-while-scan radar by using numerical data
- G01S13/726—Multiple target tracking
-
- 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
- G01S7/42—Diversity systems specially adapted for radar
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Computer Networks & Wireless Communication (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
The invention provides a multi-station radar multi-target detection method based on interference cancellation, which comprises the following implementation steps: constructing a multi-station radar target detection system; each radar station samples the received echo signals; the signal fusion center calculates an observation matrix of each spatial resolution unit; the signal fusion center calculates interference test statistics of each observation matrix; the signal fusion center calculates the test statistic of each spatial resolution unit which is not affected by interference and is affected by interference; and the signal fusion center acquires a multi-station radar multi-target detection result. The method comprises the steps of firstly judging whether the space resolution unit is affected by interference, directly constructing test statistics for target detection on the space resolution unit which is not affected by the interference, constructing a correction term for interference elimination on the space resolution unit affected by the interference, and then constructing the test statistics for target detection, thereby solving the technical problem of higher false alarm rate of the multi-station radar caused by the interference in the multi-target environment in the prior art.
Description
Technical Field
The invention belongs to the technical field of radars, and relates to a multi-station radar multi-target detection method based on interference cancellation. The method can be used for radar target detection of the multi-station radar in the environment with a plurality of moving targets, and can eliminate interference while detecting the targets.
Background
Multi-station radar systems are an important trend in future development of radar equipment. Compared to a single radar, a multi-station radar system has two prominent features: the radar stations are arranged spatially apart; and carrying out fusion or joint processing on the target information received by each radar station. It is the combination of these two unique characteristics that makes the multi-station radar system superior to the conventional single-station radar system in terms of target detection, parameter estimation, tracking filtering, synergistic interference resistance, etc. The multi-target detection method in the multi-station radar system is a detection method for judging whether targets exist or not according to echo signals received by each spatial resolution unit of a plurality of radar stations by sending data after signal processing of echo signals received by the plurality of radar stations to a signal fusion center. The test statistic of each spatial resolution unit is calculated and compared with a judgment threshold to judge the spatial resolution unit higher than the threshold, and the spatial resolution unit is detected as a target. The detection probability and the false alarm rate are two main performance indexes of the multi-station radar multi-target detection method, the detection probability is one performance index for measuring the detection precision of the multi-station radar multi-target detection method, the higher the detection probability is, the higher the detection precision is represented, and the false alarm rate refers to the probability that an actually-non-existing target is judged to be a target due to the ubiquitous and fluctuating noise when a threshold detection method is adopted in the radar detection process. In the multi-station radar multi-target detection process, it is desirable to reduce the false alarm rate while the detection probability is maximized. However, most of the existing methods only consider improving the detection probability, but do not consider reducing the false alarm rate.
For example, patent literature "multi-station radar signal level fusion target detection method based on signal-to-noise ratio information" filed by the university of western electronic technology (application No. 201910518176.9, application publication No.: CN 110161479A), a multi-station radar signal level fusion target detection method based on signal-to-noise ratio information is disclosed, firstly, selecting a detection unit, calculating local statistics of the unit at each radar station, then calculating a weighted value of each statistic according to the signal-to-noise ratio of the unit in an echo signal vector received by each radar station, finally, weighting and summing the local statistics to obtain global statistics, and making a decision in a signal fusion center, if the decision is successful, then targeting. In the method, although the detection probability of a multi-station radar system to the target is improved, in a multi-target detection environment, some space resolution units without targets can collect the observation data of the targets to form space resolution units affected by interference, so that the multi-station radar detects the space resolution units as the targets, and the reduction of the false alarm rate is affected.
Disclosure of Invention
The invention aims to overcome the defects of the prior art, and provides a multi-station radar multi-target detection method based on interference cancellation, which is used for solving the technical problem of high detection false alarm rate caused by interference influence in a multi-target environment in the prior art.
In order to achieve the above purpose, the technical scheme adopted by the invention comprises the following steps:
(1) Constructing a multi-station radar target detection system:
Constructing a multi-station radar target detection system comprising a signal fusion center, I T/R radar stations A= { A 1,A2,...,Ai,...,AI } sharing transmission and reception, and J targets distributed in a common view area of A, wherein the common view area of the radar stations A comprises G spatial resolution units C= { C (p C,1),c(pC,2),...,c(pC,g),...c(pC,G) } with the same size, each T/R radar station A i transmits M pulse signals S i＝{si,1,si,2,...,si,m,...,si,M }, I is more than or equal to 2, A i represents an ith T/R radar station, J is more than or equal to 2, G is more than or equal to 2, C (p C,g) represents a spatial resolution unit with the G center p C,g＝[xC,g,yC,g]T, x C,g、yC,g respectively represents an abscissa and an ordinate of p C,g＝[xC,g,yC,g]T, [ in ] T represents a transposition operation, M is more than or equal to 2, S i,m represents an mth pulse signal transmitted by A i;
(2) Each radar station samples the received echo signals:
Each T/R radar station A i takes T s as a sampling interval, samples the echo signals of the transmitted pulse signals S i reflected by J targets for N times to obtain an echo signal vector matrix set R= { R 1,R2,...,Ri,...,RI } corresponding to the A, and sends R to a signal fusion center, wherein 0 < N is less than or equal to [ T p/Ts],Tp ] represents a pulse repetition interval, R i represents an echo signal vector matrix corresponding to S i, and R i＝{ri,1,ri,2,…,ri,m,...,ri,M},ri,m represents an echo signal vector corresponding to S i,m;
(3) The signal fusion center calculates an observation matrix of each spatial resolution unit:
The signal fusion center calculates an observation vector Z i,g of each echo signal vector matrix R i corresponding to c (p C,g) through the center p C,g＝[xC,g,yC,g]T of each spatial resolution unit c (p C,g), and combines I observation vectors into an observation matrix Z g＝{z1,g,z2,g,...,zi,g,...,zI,g of c (p C,g);
(4) The signal fusion center calculates interference test statistics of each observation matrix:
(4a) The signal fusion center adopts a maximum likelihood estimation method to calculate interference test statistic D (Z g) of each observation matrix Z g:
Where |·| denotes a modulo operation, f i,g denotes the doppler frequency caused by the relative motion of the g-th spatial resolution unit c (p C,g) and the i-th T/R radar station a i, Representing the noise level of c (p C,g);
(4b) The signal fusion center judges whether each interference test statistic D (Z g) and a preset threshold value eta meet D (Z g) < eta, if yes, E space resolution units in a space resolution unit set C corresponding to G interference test statistic are used as space resolution units which are not affected by interference, and a set U= { C (p C,1),c(pC,2),...,c(pC,e),...,c(pC,E) }, otherwise, space resolution units corresponding to the rest Q=G-E interference test statistic are used as space resolution units affected by interference, and a set V= { C (p C,1),c(pC,2),...,c(pC,q),...,c(pC,Q) }, wherein C (p C,e) represents an E space resolution unit which is not affected by interference, and C (p C,q) represents a Q space resolution unit affected by interference;
(5) The signal fusion center calculates test statistics for each undisturbed and disturbed spatial resolution unit:
The signal fusion center calculates the test statistic L m(Ze of each spatial resolution unit c (p C,e) which is not affected by interference through a generalized likelihood ratio test method, and simultaneously calculates the test statistic L m'(Zq of each spatial resolution unit c (p C,q) which is affected by interference through a pre-constructed correction term M R(Zq), so as to realize interference elimination of c (p C,q):
Wherein, (. Cndot.) H represents a conjugate transpose operation, Z e represents an observation matrix corresponding to c (p C,e), and Z q represents an observation matrix corresponding to c (p C,q);
(6) The signal fusion center acquires a multi-station radar multi-target detection result:
The signal fusion center judges whether L m(Ze) and a preset threshold gamma m meet L m(Ze)≥γm, if yes, a target is contained in c (p C,e), if not, a target is not contained in c (p C,e), meanwhile, whether L m'(Zq)≥γm is met or not is judged, if yes, a target is contained in c (p C,q), if not, a target is not contained in c (p C,q), and J targets contained in a spatial resolution unit set U which is not affected by interference and a spatial resolution unit set V which is affected by interference are used as detection results of the multi-station radar on all targets.
Compared with the prior art, the invention has the following advantages:
In the process of acquiring the multi-target detection result of the multi-station radar, the signal fusion center firstly calculates the test statistic of each undisturbed spatial resolution unit, calculates the test statistic of each spatial resolution unit affected by interference through a pre-constructed correction term, realizes the interference elimination of the spatial resolution units affected by interference, compares the two test statistic with a preset threshold value, judges whether each spatial resolution unit contains a target, avoids the influence of the interference on the false alarm rate of the spatial resolution units under the condition of moving multi-target in the prior art, and the simulation result shows that the invention effectively reduces the false alarm rate of the multi-target detection of the multi-station radar while guaranteeing the target detection probability.
Drawings
FIG. 1 is a flow chart of an implementation of the present invention;
FIG. 2 is a graph comparing the simulation results of the false alarm rate detected by the present invention with those of the prior art;
FIG. 3 is a graph comparing the probability results of real target detection of the present invention with the prior art.
Detailed Description
The invention is described in further detail below with reference to the drawings and the specific examples.
Referring to fig. 1, the present invention includes the steps of:
Step 1) constructing a multi-station radar target detection system:
Constructing a multi-station radar target detection system comprising a signal fusion center, I T/R radar stations A= { A 1,A2,...,Ai,...,AI } sharing transmission and reception, and J targets distributed in a common view area of A, wherein the common view area of the radar stations A comprises G spatial resolution units C= { C (p C,1),c(pC,2),...,c(pC,g),...c(pC,G) } with the same size, each T/R radar station A i transmits M pulse signals S i＝{si,1,si,2,...,si,m,...,si,M }, I is more than or equal to 2, A i represents an ith T/R radar station, J is more than or equal to 2, G is more than or equal to 2, C (p C,g) represents a spatial resolution unit with the G center p C,g＝[xC,g,yC,g]T, x C,g、yC,g respectively represents an abscissa and an ordinate of p C,g＝[xC,g,yC,g]T, [ in ] T represents a transposition operation, M is more than or equal to 2, S i,m represents an mth pulse signal transmitted by A i;
the signal fusion center is a hardware device for carrying out fusion processing on detection statistics obtained by echo signals transmitted by a plurality of radar stations through signal processing and judging whether targets exist in the echo signals received by the spatial resolution units of the radar stations. Each T/R radar station can only receive its own transmitted signal and all radars operate with the same parameters. In the present embodiment, the number of radar stations i=7, the number of targets j=3, the number of pulses m=16, and the number of spatial resolution units is determined by the distance resolution, g= 1190000.
Step 2) each radar station samples the received echo signals:
Each T/R radar station A i takes T s as a sampling interval, samples the echo signals of the transmitted pulse signals S i reflected by J targets for N times to obtain an echo signal vector matrix set R= { R 1,R2,...,Ri,...,RI } corresponding to the A, and sends R to a signal fusion center, wherein 0 < N is less than or equal to [ T p/Ts],Tp ] represents a pulse repetition interval, R i represents an echo signal vector matrix corresponding to S i, and R i＝{ri,1,ri,2,…,ri,m,...,ri,M},ri,m represents an echo signal vector corresponding to S i,m;
The calculation formula of the echo signal vector matrix R i is as follows:
τi,j＝Ri,j(pT,j)/c
where α i,j denotes the complex scattering coefficient, k=1,..m, d i,j (·) denotes the doppler vector, f i,j denotes the doppler frequency caused by the relative motion of the jth target and the ith T/R radar station a i, p T,j denotes the spatial resolution unit in which the target is located, Representing additive noise, ω i,m represents noise within the mth pulse of A i, each element of ω i,m being 0 in mean and/>, varianceΤ i,j represents the time delay of the jth target and the ith T/R radar station a i, c represents the speed of light, R i,j(pT,j) represents the distance of the jth target and the ith T/R radar station a i.
Step 3) the signal fusion center calculates an observation matrix of each spatial resolution unit:
The signal fusion center calculates an observation vector Z i,g of each echo signal vector matrix R i corresponding to c (p C,g) through the center p C,g＝[xC,g,yC,g]T of each spatial resolution unit c (p C,g), and combines I observation vectors into an observation matrix Z g＝{z1,g,z2,g,...,zi,g,...,zI,g of c (p C,g);
The calculation formula of the observation vector z i,g of each echo signal vector matrix R i corresponding to c (p C,g) is as follows:
Where s i,k(pC,g) represents a kth pulse signal transmitted by a i corresponding to the g-th spatial resolution unit c (p C,g), θ (p C,g) represents an angle of c (p C,g), θ 0 represents a transmit beam direction, and Δθ represents a transmit beam width.
Step 4) the signal fusion center calculates interference test statistics of each observation matrix:
Step 4 a), the signal fusion center calculates interference test statistic D (Z g) of each observation matrix Z g by adopting a maximum likelihood estimation method:
Where |·| denotes a modulo operation, f i,g denotes the doppler frequency caused by the relative motion of the g-th spatial resolution unit c (p C,g) and the i-th T/R radar station a i, Representing the noise level of c (p C,g);
Step 4 b), the signal fusion center judges whether each interference test statistic D (Z g) and a preset threshold value eta meet D (Z g) < eta, if yes, E in a spatial resolution unit set C corresponding to G interference test statistic are used as spatial resolution units which are not affected by interference, and a set U= { C (p C,1),c(pC,2),...,c(pC,e),...,c(pC,E) }, otherwise, the rest spatial resolution units corresponding to Q=G-E interference test statistic are used as spatial resolution units which are affected by interference, and a set V= { C (p C,1),c(pC,2),...,c(pC,q),...,c(pC,Q) }, wherein C (p C,e) represents an E-th spatial resolution unit which is not affected by interference, and C (p C,q) represents a Q-th spatial resolution unit which is affected by interference;
where η is designed by the nomann pearson criterion.
Step 5) the signal fusion center calculates the test statistic of each spatial resolution unit which is not affected by interference and is affected by interference:
The signal fusion center calculates the test statistic L m(Ze of each spatial resolution unit c (p C,e) which is not affected by interference through a generalized likelihood ratio test method, and simultaneously calculates the test statistic L m'(Zq of each spatial resolution unit c (p C,q) which is affected by interference through a pre-constructed correction term M R(Zq), so as to realize interference elimination of c (p C,q):
Wherein, (. Cndot.) H represents a conjugate transpose operation, Z e represents an observation matrix corresponding to c (p C,e), and Z q represents an observation matrix corresponding to c (p C,q);
step 6), the signal fusion center acquires a multi-station radar multi-target detection result:
The signal fusion center judges whether L m(Ze) and a preset threshold gamma m meet L m(Ze)≥γm, if yes, a target is contained in c (p C,e), if not, a target is not contained in c (p C,e), meanwhile, whether L m'(Zq)≥γm is met or not is judged, if yes, a target is contained in c (p C,q), if not, a target is not contained in c (p C,q), and J targets contained in a spatial resolution unit set U which is not affected by interference and a spatial resolution unit set V which is affected by interference are used as detection results of the multi-station radar on all targets.
The technical effects of the present invention will be described with reference to the following simulation experiments.
1. Simulation conditions and content:
The simulation adopts CPU as Intel Core i7-7700, RAM as 8GB,64 bit operating system and Microsoft windows professional version Matlab R2017b simulation software.
The multi-station radar system adopted by the simulation comprises 7T/R stations which 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 public monitored area, and the position coordinates of the targets are (49,1.2) km, (50,2.0) km and (52,1.6) km and the speed information is (-100, 0) km/s, (-50, 50) km/s and (-100, 50) km/s. The signal bandwidth is 5MHz, the duration is τ=51μs, the carrier frequency is f c =1 GHz, the number of pulses is m=16, pri is T p =0.25 ms, and the beam width is 4 °.
The false alarm rate and the real target detection probability of the multi-station radar signal level fusion target detection method based on the signal-to-noise ratio information are respectively compared and simulated, and the results are shown in fig. 2 and 3.
2. Simulation result analysis:
referring to fig. 2, the abscissa in the drawing represents the X-axis coordinates of the spatially resolved unit position in km, and the ordinate represents the Y-axis coordinates of the spatially resolved unit position in km. Wherein fig. 2 (a) shows the detection result of the object detection in the prior art, each straight line in the drawing is composed of a true object and a false object generated by interference, and the intersection point of the straight lines, that is, the point surrounded by a circle, represents the spatial unit where the object is located. FIG. 2 (b) shows the detection result of the object detection of the present invention, wherein the circled points in the figure represent the spatial units where the object is located.
As can be seen from fig. 2 (a), the prior art test result diagram has targets at three target positions, namely, (49,1.2) km, (50,2.0) km and (52,1.6) km, and a large number of decoys at other positions. As can be seen from FIG. 2 (b), the detection result graph adopting the invention has targets only at three target positions of (49,1.2) km, (50,2.0) km and (52,1.6) km, and no decoy exists at other positions. The invention can effectively eliminate interference, inhibit false target generation and reduce false alarm rate.
Referring to fig. 3, the abscissa represents signal-to-noise ratio in dB, the ordinate represents target detection probability, the curve marked with hexagram, square, and filled circle represents a target detection probability curve for detecting different targets using the prior art, the curve marked with open circle, cross, filled point represents a target detection probability curve for detecting different targets using the present invention. The downward triangle, asterisk, cross-character are labeled and the curve of P e＝10-2 represents the target detection probability curve for target detection of different targets by the invention. The calculation formula of the target detection probability is as follows:
Wherein, P e represents the probability that the interfered spatial resolution unit is judged as the target spatial resolution unit, P d represents the detection probability of the target, n d represents the number of times the target is detected in the experiment, C d represents the number of times of each signal-to-noise ratio experiment, and each signal-to-noise ratio experiment number of the simulation experiment 2 of the invention is 1000.
As can be seen from fig. 3, at P e＝10-1, the true object detection probability curve of the present invention is slightly lower than that of the prior art, because the erroneous decision in the discrimination results in energy accumulation loss. At P e＝10-2, the method is the same as the detection probability curve of the existing method. Thus, P e needs to be small enough to maintain good performance for target detection. Meanwhile, when the signal-to-noise ratio is larger than 4dB, the true target detection probability is always maintained to be more than 99%, and the method is proved to be capable of eliminating the influence of interference under the condition of keeping the true target detection probability, and solves the problem of excessively high false alarm rate caused by interference in the prior art.
Claims (3)
1. The multi-station radar multi-target detection method based on interference cancellation is characterized by comprising the following steps:
(1) Constructing a multi-station radar target detection system:
Constructing a multi-station radar target detection system comprising a signal fusion center, I T/R radar stations A= { A 1,A2,...,Ai,...,AI } sharing transmission and reception, and J targets distributed in a common view area of A, wherein the common view area of the radar stations A comprises G spatial resolution units C= { C (p C,1),c(pC,2),...,c(pC,g),...c(pC,G) } with the same size, each T/R radar station A i transmits M pulse signals S i＝{si,1,si,2,...,si,m,...,si,M }, I is more than or equal to 2, A i represents an ith T/R radar station, J is more than or equal to 2, G is more than or equal to 2, C (p C,g) represents a spatial resolution unit with the G center p C,g＝[xC,g,yC,g]T, x C,g、yC,g respectively represents an abscissa and an ordinate of p C,g＝[xC,g,yC,g]T, [ in ] T represents a transposition operation, M is more than or equal to 2, S i,m represents an mth pulse signal transmitted by A i;
(2) Each radar station samples the received echo signals:
Each T/R radar station A i takes T s as a sampling interval, samples the echo signals of the transmitted pulse signals S i reflected by J targets for N times to obtain an echo signal vector matrix set R= { R 1,R2,...,Ri,...,RI } corresponding to the A, and sends R to a signal fusion center, wherein 0 < N is less than or equal to [ T p/Ts],Tp ] represents a pulse repetition interval, R i represents an echo signal vector matrix corresponding to S i, and R i＝{ri,1,ri,2,…,ri,m,...,ri,M},ri,m represents an echo signal vector corresponding to S i,m;
(3) The signal fusion center calculates an observation matrix of each spatial resolution unit:
The signal fusion center calculates an observation vector Z i,g of each echo signal vector matrix R i corresponding to c (p C,g) through the center p C,g＝[xC,g,yC,g]T of each spatial resolution unit c (p C,g), and combines I observation vectors into an observation matrix Z g＝{z1,g,z2,g,...,zi,g,...,zI,g of c (p C,g);
(4) The signal fusion center calculates interference test statistics of each observation matrix:
(4a) The signal fusion center adopts a maximum likelihood estimation method to calculate interference test statistic D (Z g) of each observation matrix Z g:
Where |·| denotes a modulo operation, f i,g denotes the doppler frequency caused by the relative motion of the g-th spatial resolution unit c (p C,g) and the i-th T/R radar station a i, Representing the noise level of c (p C,g);
(4b) The signal fusion center judges whether each interference test statistic D (Z g) and a preset threshold value eta meet D (Z g) < eta, if yes, E space resolution units in a space resolution unit set C corresponding to G interference test statistic are used as space resolution units which are not affected by interference, and a set U= { C (p C,1),c(pC,2),...,c(pC,e),...,c(pC,E) }, otherwise, space resolution units corresponding to the rest Q=G-E interference test statistic are used as space resolution units affected by interference, and a set V= { C (p C,1),c(pC,2),...,c(pC,q),...,c(pC,Q) }, wherein C (p C,e) represents an E space resolution unit which is not affected by interference, and C (p C,q) represents a Q space resolution unit affected by interference;
(5) The signal fusion center calculates test statistics for each undisturbed and disturbed spatial resolution unit:
The signal fusion center calculates the test statistic L m(Ze of each spatial resolution unit c (p C,e) which is not affected by interference through a generalized likelihood ratio test method, and simultaneously calculates the test statistic L m'(Zq of each spatial resolution unit c (p C,q) which is affected by interference through a pre-constructed correction term M R(Zq), so as to realize interference elimination of c (p C,q):
Wherein, (. Cndot.) H represents a conjugate transpose operation, Z e represents an observation matrix corresponding to c (p C,e), and Z q represents an observation matrix corresponding to c (p C,q);
(6) The signal fusion center acquires a multi-station radar multi-target detection result:
The signal fusion center judges whether L m(Ze) and a preset threshold gamma m meet L m(Ze)≥γm, if yes, a target is contained in c (p C,e), if not, a target is not contained in c (p C,e), meanwhile, whether L m'(Zq)≥γm is met or not is judged, if yes, a target is contained in c (p C,q), if not, a target is not contained in c (p C,q), and J targets contained in a spatial resolution unit set U which is not affected by interference and a spatial resolution unit set V which is affected by interference are used as detection results of the multi-station radar on all targets.
2. The interference cancellation-based multi-station radar multi-target detection method of claim 1, wherein: the echo signal vector matrix R i in the step (2) has a calculation formula:
τi,j＝Ri,j(pT,j)/c
where α i,j denotes the complex scattering coefficient, k=1,..m, d i,j (·) denotes the doppler vector, f i,j denotes the doppler frequency caused by the relative motion of the jth target and the ith T/R radar station a i, p T,j denotes the spatial resolution unit in which the target is located, Representing additive noise, ω i,m represents noise within the mth pulse of A i, each element of ω i,m being 0 in mean and/>, varianceΤ i,j represents the time delay of the jth target and the ith T/R radar station a i, c represents the speed of light, R i,j(pT,j) represents the distance of the jth target and the ith T/R radar station a i.
3. The interference cancellation-based multi-station radar multi-target detection method of claim 1, wherein: the observation vector z i,g of each echo signal vector matrix R i corresponding to the calculation c (p C,g) in the step (3) is calculated according to the following formula:
Where s i,k(pC,g) represents a kth pulse signal transmitted by a i corresponding to the g-th spatial resolution unit c (p C,g), θ (p C,g) represents an angle of c (p C,g), θ 0 represents a transmit beam direction, and Δθ represents a transmit beam width.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111231826.5A CN113960536B (en) | 2021-10-22 | 2021-10-22 | Multi-station radar multi-target detection method based on interference elimination |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202111231826.5A CN113960536B (en) | 2021-10-22 | 2021-10-22 | Multi-station radar multi-target detection method based on interference elimination |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN113960536A CN113960536A (en) | 2022-01-21 |
| CN113960536B true CN113960536B (en) | 2024-05-14 |
Family
ID=79466053
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202111231826.5A Active CN113960536B (en) | 2021-10-22 | 2021-10-22 | Multi-station radar multi-target detection method based on interference elimination |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN113960536B (en) |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2391022A1 (en) * | 2010-05-27 | 2011-11-30 | Mitsubishi Electric R&D Centre Europe B.V. | Classification of interference |
| CN103954939A (en) * | 2014-01-21 | 2014-07-30 | 中国人民解放军海军航空工程学院 | Smart-noise-jamming resistant method based on radar networking |
| CN104991233A (en) * | 2015-06-29 | 2015-10-21 | 西安电子科技大学 | Networking radar anti-cheating interference method based on signal level fusion |
| CN105607045A (en) * | 2016-01-11 | 2016-05-25 | 西安电子科技大学 | Optimized station distribution method for netted radar unit under deceptive jamming |
| CN105842674A (en) * | 2016-04-18 | 2016-08-10 | 南京工程学院 | Statistical MIMO radar multi-target detection simulation method |
| CN111896928A (en) * | 2020-08-10 | 2020-11-06 | 西安电子科技大学 | Multi-station radar target detection method based on active deception jamming elimination |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE102019114551A1 (en) * | 2019-05-29 | 2020-12-03 | Infineon Technologies Ag | DETECTION OF INTERFERENCE-RELATED INTERFERENCE IN FMCW RADAR SYSTEMS |
-
2021
- 2021-10-22 CN CN202111231826.5A patent/CN113960536B/en active Active
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| EP2391022A1 (en) * | 2010-05-27 | 2011-11-30 | Mitsubishi Electric R&D Centre Europe B.V. | Classification of interference |
| CN103954939A (en) * | 2014-01-21 | 2014-07-30 | 中国人民解放军海军航空工程学院 | Smart-noise-jamming resistant method based on radar networking |
| CN104991233A (en) * | 2015-06-29 | 2015-10-21 | 西安电子科技大学 | Networking radar anti-cheating interference method based on signal level fusion |
| CN105607045A (en) * | 2016-01-11 | 2016-05-25 | 西安电子科技大学 | Optimized station distribution method for netted radar unit under deceptive jamming |
| CN105842674A (en) * | 2016-04-18 | 2016-08-10 | 南京工程学院 | Statistical MIMO radar multi-target detection simulation method |
| CN111896928A (en) * | 2020-08-10 | 2020-11-06 | 西安电子科技大学 | Multi-station radar target detection method based on active deception jamming elimination |
Non-Patent Citations (3)
| Title |
|---|
| "Centralized multiple moving target detection using multistatic radar system";Shiyu Zhang等;《2021 CIE International conference on radar》;20211215;第2600-2603页 * |
| "Target detection for multistatic radar in the presence of deception jamming";Shiyu Zhang等;《IEEE sensors journal》;20210331;第21卷(第6期);第2600-2603页 * |
| 对组网雷达的多假目标欺骗干扰技术;朱宇;罗景青;田玮;;电光与控制;20130829(09);全文 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN113960536A (en) | 2022-01-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN105807267B (en) | A kind of MIMO radar extends mesh object detection method | |
| CN109444820B (en) | Method for detecting target after interference suppression of multi-channel radar when clutter and interference coexist | |
| CN111239727B (en) | Passenger counting method and communication equipment | |
| CN113238211B (en) | Parameterized adaptive array signal detection method and system under interference condition | |
| CN108983165B (en) | Substation selection-based anti-deception jamming method for multi-station radar system | |
| CN109143195A (en) | Radar target detection method based on full KL divergence | |
| CN103913725A (en) | Aircraft radar ground moving target detection method under intensive forwarding type interference environment | |
| CN111896928B (en) | Multi-station radar target detection method based on active deception interference elimination | |
| CN103901409A (en) | Airborne radar anti-forwarding type interference method based on adaptive beamforming | |
| CN112198487B (en) | Target detection method under clutter background of wind power plant | |
| CN112147584A (en) | MIMO radar extended target detection method based on non-uniform clutter | |
| CN109765529A (en) | A kind of millimetre-wave radar anti-interference method and system based on digital beam froming | |
| CN108318877A (en) | Object detection method under clutter subspace based on multistatic radar | |
| CN108572353B (en) | Pulse time sequence planning method for low-interception radar | |
| CN116165610A (en) | Sea clutter suppression algorithm for improving singular value decomposition | |
| CN113960536B (en) | Multi-station radar multi-target detection method based on interference elimination | |
| CN113608193A (en) | Radar multi-target distance and speed estimation method based on UNet | |
| CN113093174B (en) | PHD filter radar fluctuation weak multi-target-based pre-detection tracking method | |
| CN106019250A (en) | Repeating false target discriminating method based on angular glint | |
| CN114325599B (en) | Automatic threshold detection method for different environments | |
| CN110244289A (en) | A kind of adaptive particle filter ground wave radar target integrative detection method | |
| CN113534132B (en) | Adaptive unmanned aerial vehicle direction of arrival estimation method | |
| CN115754970B (en) | Space-time adaptive target detection method and system for distributed unmanned aerial vehicle radar | |
| CN115754970A (en) | Space-time self-adaptive target detection method and system for distributed unmanned airborne radar | |
| CN114252856A (en) | MIMO radar self-adaptive detection method based on prior knowledge assistance |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |