CN109633591B - External radiation source radar double-base-distance positioning method under observation station position error - Google Patents

External radiation source radar double-base-distance positioning method under observation station position error Download PDF

Info

Publication number
CN109633591B
CN109633591B CN201910048330.0A CN201910048330A CN109633591B CN 109633591 B CN109633591 B CN 109633591B CN 201910048330 A CN201910048330 A CN 201910048330A CN 109633591 B CN109633591 B CN 109633591B
Authority
CN
China
Prior art keywords
observation station
target
radiation source
external radiation
double
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
Application number
CN201910048330.0A
Other languages
Chinese (zh)
Other versions
CN109633591A (en
Inventor
左燕
周夏磊
陈志峰
郭云飞
刘俊
Current Assignee (The listed assignees may be inaccurate. Google has not performed a legal analysis and makes no representation or warranty as to the accuracy of the list.)
Hangzhou Dianzi University
Original Assignee
Hangzhou Dianzi University
Priority date (The priority date 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 date listed.)
Filing date
Publication date
Application filed by Hangzhou Dianzi University filed Critical Hangzhou Dianzi University
Priority to CN201910048330.0A priority Critical patent/CN109633591B/en
Publication of CN109633591A publication Critical patent/CN109633591A/en
Application granted granted Critical
Publication of CN109633591B publication Critical patent/CN109633591B/en
Active legal-status Critical Current
Anticipated expiration legal-status Critical

Links

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
    • G01S7/41—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
    • G01S7/411—Identification of targets based on measurements of radar reflectivity

Abstract

The invention discloses a double-base-distance positioning method for an external radiation source radar under an observation station position error. According to the obtained double-base-distance measurement information, the intermediate variable is introduced to convert the nonlinear equation into a pseudo-linear equation, and a target position estimation model is established. And designing weight according to the double-base-distance measurement error and the observation station position error, and estimating by adopting an iterative weighted least square method. And then, a correlation least square estimation model is constructed by considering the correlation between the intermediate variable and the target position, and the target position estimation result is improved. The invention introduces auxiliary variables, reasonably converts the nonlinear measurement model into a pseudo-linear estimation model, and reduces the complexity of external radiation source positioning on the premise of ensuring the estimation performance. And optimizing the index weight according to the position error of the observation station and the double-base distance measurement noise design, thereby reducing the influence of the error on the target positioning performance and improving the target position estimation precision. The method and the device have the advantage that the positioning estimation of the target position is more accurate through two steps of iteration.

Description

External radiation source radar double-base-distance positioning method under observation station position error
Technical Field
The invention belongs to the technical field of passive positioning of sensors, and particularly relates to a double-base-distance positioning method for an external radiation source radar under an observation station position error.
Background
The external radiation source radar utilizes a third-party non-cooperative signal source (such as a mobile phone communication signal, a television broadcast signal, enemy radar information and the like) as an opportunity radiation source of a target, and receives a signal emitted by a radiation source of the third party scattered by the target through an observation station (a receiving station) to realize the detection and the positioning of the target. Because the external radiation source radar does not emit electromagnetic signals, the external radiation source radar has the advantages of good concealment, strong anti-interference capability, wide monitoring range, low cost and the like. The external radiation source radar system is used as a sensor networking system with a double/multi-base structure, and positioning and tracking of a target are realized through data fusion processing.
In the practical application of an external radiation source radar system, an observation station is often installed on a satellite, an airplane, a naval vessel or a ground vehicle and other moving platforms, the position of the observation station cannot be accurately obtained, and estimation errors exist. Ignoring the sensor position deviation results in degraded target positioning performance. The passive positioning of the target by using the double-base-distance measurement of the external radiation source radar under the condition that the position of the observation station has errors is a key technology for data processing of the external radiation source radar system.
At present, a passive positioning method under the position error of an observation station mainly focuses on the research of the positioning problem of a target radiation source. A Wanding team of the information engineering institute of liberation provides an iterative positioning algorithm based on Taylor series aiming at the positioning problem of a target radiation source under the condition that the position error of an observation station is considered. A K.C.Ho team of the university of Missouri in America provides a two-step weighted least square estimation algorithm aiming at the problem of positioning of a target radiation source under the position error of an observation station. A naval engineering university Chenshaochang team provides an algorithm based on constrained total least square aiming at a target radiation source positioning problem under the condition of sensor position errors. Different from the positioning problem of a target radiation source, the external radiation source radar adopts a double/multiple base structure to obtain double base distance measurement. The target positioning is carried out by utilizing the double base distances, and the nonlinearity degree is increased. At present, most of external radiation source radar double-base-distance positioning problems do not consider the influence of observation station position errors. The invention provides a double-base-distance positioning method of an external radiation source radar under the position error of an observation station.
Disclosure of Invention
The invention provides a double-base-distance positioning method of an external radiation source radar under an observation station position error, aiming at a multi-transmitting single-receiving external radiation source radar, and considering the influence of the observation station position error on the positioning performance. Constructing an intermediate variable, carrying out pseudo-linearization on a nonlinear double-base-distance equation to construct a linear estimation equation, designing weights according to a double-base-distance measurement error and an observation station position error, and obtaining optimal estimation by adopting an iterative weighted second-most-product estimation method. On the basis, the correlation between the intermediate variable and the target position is considered, and a correlation least square estimation method is designed, so that the target estimation performance is further improved.
The method comprises the following specific steps:
step 1, in a multi-shot single-shot external radiation source radar network (M external radiation sources and an observation station), external radiation source signals are reflected to the observation station through a target, and double-base-distance information is obtained;
step 2, introducing an intermediate variable into the double-base-distance measurement model
Figure BDA0001949942380000021
Neglecting the influence of measurement noise and observation station position error, converting the double-base-distance nonlinear equation intoThe equation Z is converted into a pseudo linear equation HX;
and 3, considering the influence of the measurement error and the position error of the observation station on the coefficient matrixes H and Z, extracting the H and Z noise components in the double-base-distance error pseudo-linear equation Z-HX, and constructing a pseudo-linear equation as follows:
1＝Z1-H1X1＝A1n+B1ΔSr
step 4, designing weights according to the position errors of the observation stations and the double-base distance measurement errors, and obtaining an estimated value of the target position by adopting a weighted least square estimation algorithm:
XWLS＝(H1 TW1H1)-1H1 TW1Z1
and 5, on the basis of the estimation result, considering the correlation between the variables to be solved, and improving the estimation value in the step 4 by adopting a correlation least square estimation algorithm.
The invention has the beneficial effects that:
1. by introducing an intermediate variable, a nonlinear double-base-distance measurement model is reasonably converted into a pseudo-linear estimation model, and a closed analytic solution of target position estimation is obtained.
2. And optimizing the index weight according to the position error of the observation station and the double-base distance measurement noise design, thereby reducing the influence of the error on the target positioning performance and improving the target position estimation precision.
3. And (4) considering the correlation between the intermediate variable and the variable to be solved, designing a correlation weighted least square algorithm, and further reducing the estimation error.
The specific implementation mode is as follows:
the invention designs an external radiation source radar double-base-distance positioning method under the position error of an observation station, which is used for positioning a target in a radar network system of an external radiation source by using double-base-distance information obtained by the observation station and comprises the following steps:
step 1: in the multi-emission single-emission external radiation source radar network, M external radiation sources and an observation station are included. The real position of the observation station is located at the origin
Figure BDA0001949942380000022
Nominal position S of observation stationr＝[x0,y0]TThen, then
Figure BDA0001949942380000023
ΔSrIs the position error vector of the observation station and is assumed to be independent white Gaussian zero mean noise with covariance of
Figure BDA0001949942380000031
The m-th emission source has a coordinate vector of
Figure BDA0001949942380000032
P targets, the coordinate vector of the P-th target being
Figure BDA0001949942380000033
A single observation station is used for receiving the difference between a reflection signal of an irradiated target from an external radiation source and a direct wave signal of the external radiation source to obtain double-base-distance information
Figure BDA0001949942380000034
Wherein, | | · | | is an euclidean distance; the number of emission sources is M, and the number of targets is P; u. ofm,pRepresenting the measured double-base distance of the target p by an external radiation source radar system consisting of the emission source m and the observation station; n ism,pExpressing the double-base distance measurement error of the target p measured by the external radiation source radar system consisting of the emission source m and the observation station, assuming nm,pIs independent white Gaussian zero mean noise with covariance of Qn。
Step 2: introducing intermediate variables into a double-base-distance measurement model
Figure BDA0001949942380000035
Neglecting the measurement noise nm,pAnd Δ SrThe above nonlinear equation (1) is converted into a pseudo linear equation in the form of
Figure BDA0001949942380000036
Wherein the content of the first and second substances,
Figure BDA0001949942380000037
writing equation (2) in matrix form, as follows
Z＝HX(3)
Wherein the content of the first and second substances,
Figure BDA0001949942380000038
H＝[blkdiag(h(1),…h(P))]，
Figure BDA0001949942380000039
obtaining an estimate of a target using a least squares estimate
Figure BDA00019499423800000310
And step 3: and (4) considering the influence of the measurement error and the observation station position error on H and Z, extracting H and Z noise components in the double-base-distance error pseudo-linear equation (3) and constructing a target position pseudo-linear estimation equation. Will be provided with
Figure BDA0001949942380000041
Brought into formula (2) and unfolded to obtain
Figure BDA0001949942380000042
Wherein the content of the first and second substances,
Figure BDA0001949942380000043
Figure BDA0001949942380000044
writing equation (5) in matrix form:
1＝Z1-H1X1＝A1n+B1ΔSr(6)
wherein the content of the first and second substances,
Figure BDA0001949942380000045
H1＝[blkdiag(h1(1),…h1(P))]，
Figure BDA0001949942380000046
Figure BDA0001949942380000047
n＝diag{n1,1… nm,p}，
Figure BDA0001949942380000048
and 4, step 4: and designing weights according to the position errors of the observation station and the double-base distance measurement errors, and obtaining an estimated value of the target position by adopting a weighted least square estimation algorithm.
Step 4.1: and (5) initializing. Let the iteration number k be 0, and use the least square estimation value obtained by equation (4) as the target initial estimation value
Figure BDA0001949942380000051
Step 4.2: by
Figure BDA0001949942380000052
Estimated value calculation coefficient matrix H1，Z1，A1And B1. Optimizing index weight according to observation station position error and double-base-distance measurement noise design
Figure BDA0001949942380000053
Step 4.3: let k be k +1, estimate by weighted least squares
Figure BDA0001949942380000054
Obtaining a position estimate of an object
Figure BDA0001949942380000055
And an estimate of the intermediate variable
Figure BDA0001949942380000056
Step 4.4: judgment of
Figure BDA0001949942380000057
And is
Figure BDA0001949942380000058
Wherein eta1And η2Is a threshold value; if the condition algorithm iteration is satisfied and stopped, obtaining the position weighted least square estimation value of the target
Figure BDA0001949942380000059
Otherwise, go to step 4.2.
And 5: taking into account the intermediate variable Rp(k) And target position
Figure BDA00019499423800000510
The correlation between the two is designed, and the estimated value X of the correlation least square algorithm to the step 4 is designedWLSAnd (5) carrying out improvement.
Step 5.1: constructing a correlated least squares estimation model
2＝Z2-H2X2＝A2ΔX1+B2ΔSr(7)
Wherein, X2＝[(x1-x0)2(y1-y0)2… (xP-x0)2(yP-y0)2]T，
Figure BDA00019499423800000518
H2＝blkdiag(h2(1)…h2(P))，
Figure BDA00019499423800000511
A2＝2diag[(x1-x0) (y1-y0) R1… (xP-x0) (yP-y0) RP]，
Figure BDA00019499423800000512
Figure BDA00019499423800000513
Figure BDA00019499423800000514
Figure BDA00019499423800000515
Is XWLSX ofp(k) The items are,
Figure BDA00019499423800000516
about XWLSY of (A) to (B)p(k) The items are,
Figure BDA00019499423800000517
about XWLSR of (A) to (B)p(k) An item.
Step 5.2: from observation station position error Δ SrCovariance and target state X1Design weight of covariance of estimated error W2＝E[2 2 T]＝(A2cov(X1)A2 T+B2QSB2 T)-1，
Figure BDA0001949942380000064
Is in a target state X1The estimated error covariance of (2).
Step 5.3: obtaining the estimation value of the target position square term by adopting a weighted least square method estimation calculation method
Figure BDA0001949942380000061
Step 5.4: x2The medium variable is the square term of the difference between the target position and the observation station position, and the position required to obtain the target needs to be X2The root number is as follows:
Figure BDA0001949942380000062
wherein II ═ diag { sgn (X)1(3p-2)-x0)sgn(X1(3p-1)-y0) And } sgn (·) is a sign function.
Finally, the target position estimation under the observation station position error is obtained
Figure BDA0001949942380000063

Claims (1)

1. A double base distance positioning method of an external radiation source radar under observation station position errors is characterized by comprising the following steps: the method comprises the following steps:
step 1: in the multi-emission single-emission external radiation source radar network, the multi-emission single-emission external radiation source radar network comprises M external radiation sources and an observation station; the real position of the observation station is located at the origin
Figure FDA0002600416820000011
Nominal position S of observation stationr＝[x0,y0]TThen, then
Figure FDA0002600416820000012
ΔSrIs the position error vector of the observation station and is assumed to be independent white Gaussian zero mean noise with covariance of E [ Delta S ]rΔSr T]＝QS(ii) a The m < th > external radiation source has a coordinate vector of
Figure FDA0002600416820000013
P targets, the coordinate vector of the P-th target being
Figure FDA0002600416820000014
A single observation station is used for receiving the difference between a reflection signal of an irradiated target from an external radiation source and a direct wave signal of the external radiation source to obtain double-base-distance information
Figure FDA0002600416820000015
Wherein, | | · | | is an euclidean distance; the number of external radiation sources is M, and the number of targets is P; u. ofm,pRepresenting the measured double-base distance of the target p by an external radiation source radar system consisting of an external radiation source m and an observation station; n ism,pExpressing the double-base distance measurement error of the external radiation source radar system formed by the external radiation source m and the observation station to the target p, assuming nm,pIs independent white Gaussian zero mean noise with covariance of Qn；
Step 2: introducing intermediate variables into a double-base-distance measurement model
Figure FDA0002600416820000016
Neglecting the measurement noise nm,pAnd Δ SrConverting the non-linear equation (1) into a pseudo-linear equation of the form
Figure FDA0002600416820000017
Wherein the content of the first and second substances,
Figure FDA0002600416820000018
Figure FDA0002600416820000019
writing equation (2) in matrix form, as follows
Z＝HX (3)
Wherein the content of the first and second substances,
Figure FDA0002600416820000021
H＝[blkdiag(h(1),…h(P))]，
Figure FDA0002600416820000022
obtaining an estimate of a target using a least squares estimate
Figure FDA0002600416820000023
And step 3: considering the influence of the measurement error and the position error of the observation station on H and Z, extracting H and Z noise components in the double-base-distance error pseudo-linear equation (3) and constructing a target position pseudo-linear estimation equation; will be provided with
Figure FDA0002600416820000024
And
Figure FDA0002600416820000025
brought into formula (2) and unfolded to obtain
Figure FDA0002600416820000026
Wherein the content of the first and second substances,
Figure FDA0002600416820000027
Figure FDA0002600416820000028
writing equation (5) in matrix form:
1＝Z1-H1X1＝A1n+B1ΔSr(6)
wherein the content of the first and second substances,
Figure FDA0002600416820000031
H1＝[blkdiag(h1(1),…h1(P))]，
Figure FDA0002600416820000032
Figure FDA0002600416820000033
n＝diag{n1,1…nm,p}，
Figure FDA0002600416820000034
and 4, step 4: designing weights according to the position errors of the observation station and the double-base distance measurement errors, and obtaining an estimated value of a target position by adopting a weighted least square estimation algorithm;
step 4.1: initializing; let the iteration number k be 0, and use the least square estimation value obtained by equation (4) as the target initial estimation value
Figure FDA0002600416820000035
Step 4.2: by
Figure FDA0002600416820000036
Estimated value calculation coefficient matrix H1，Z1，A1And B1(ii) a Optimizing index weight according to observation station position error and double-base-distance measurement noise design
Figure FDA0002600416820000037
Step 4.3: let k be k +1, estimate by weighted least squares
Figure FDA0002600416820000038
Obtaining a position estimate of an object
Figure FDA0002600416820000039
Regulating stomachEstimate of inter-variables
Figure FDA00026004168200000310
Step 4.4: judgment of
Figure FDA00026004168200000311
And is
Figure FDA00026004168200000312
Wherein eta1And η2Is a threshold value; if the condition algorithm iteration is satisfied and stopped, obtaining the position weighted least square estimation value of the target
Figure FDA00026004168200000313
Otherwise, turning to step 4.2;
and 5: taking into account the intermediate variable Rp(k) And target position
Figure FDA0002600416820000041
The correlation between the two is designed, and the estimated value X of the correlation least square algorithm to the step 4 is designedWLSCarrying out improvement;
step 5.1: constructing a correlated least squares estimation model
2＝Z2-H2X2＝A2ΔX1+B2ΔSr(7)
Wherein, X2＝[(x1-x0)2(y1-y0)2…(xP-x0)2(yP-y0)2]T，Z2＝[z2(1)…z2(P)]T，
Figure FDA0002600416820000042
H2＝blkdiag(h2(1)…h2(P))，
Figure FDA0002600416820000043
A2＝2diag[(x1-x0) (y1-y0) R1…(xP-x0) (yP-y0) RP]，
Figure FDA0002600416820000044
Figure FDA0002600416820000045
Figure FDA0002600416820000046
Figure FDA0002600416820000047
Is XWLSX ofp(k) The items are,
Figure FDA0002600416820000048
about XWLSY of (A) to (B)p(k) The items are,
Figure FDA0002600416820000049
about XWLSR of (A) to (B)p(k) An item;
step 5.2: from observation station position error Δ SrCovariance and target state X1Design weight of covariance of estimated error W2＝E[2 2 T]＝(A2cov(X1)A2 T+B2QSB2 T)-1，
Figure FDA00026004168200000410
Is in a target state X1The estimated error covariance of (a);
step 5.3: obtaining the estimation value of the target position square term by adopting a weighted least square method estimation calculation method
Figure FDA00026004168200000411
Step 5.4: x2The medium variable is the square term of the difference between the target position and the observation station position, and the position required to obtain the target needs to be X2The root number is as follows:
Figure FDA00026004168200000412
wherein, ii ═ diag { sgn (X)1(3p-2)-x0) sgn(X1(3p-1)-y0) -sgn (·) is a sign function;
finally, the target position estimation under the observation station position error is obtained
Figure FDA0002600416820000051
CN201910048330.0A 2019-01-18 2019-01-18 External radiation source radar double-base-distance positioning method under observation station position error Active CN109633591B (en)

Priority Applications (1)

Application Number Priority Date Filing Date Title
CN201910048330.0A CN109633591B (en) 2019-01-18 2019-01-18 External radiation source radar double-base-distance positioning method under observation station position error

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
CN201910048330.0A CN109633591B (en) 2019-01-18 2019-01-18 External radiation source radar double-base-distance positioning method under observation station position error

Publications (2)

Publication Number Publication Date
CN109633591A CN109633591A (en) 2019-04-16
CN109633591B true CN109633591B (en) 2020-11-06

Family

ID=66062162

Family Applications (1)

Application Number Title Priority Date Filing Date
CN201910048330.0A Active CN109633591B (en) 2019-01-18 2019-01-18 External radiation source radar double-base-distance positioning method under observation station position error

Country Status (1)

Country Link
CN (1) CN109633591B (en)

Families Citing this family (8)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN110426672B (en) * 2019-07-23 2021-05-04 江南大学 Double-iteration positioning system based on interval analysis and application thereof
CN110389327A (en) * 2019-07-29 2019-10-29 杭州电子科技大学 The more external illuminators-based radars of multistation are biradical away from localization method under receiving station's location error
CN110389326A (en) * 2019-07-29 2019-10-29 杭州电子科技大学 The more external illuminators-based radar moving target localization methods of multistation under a kind of reception station error
CN110412501A (en) * 2019-08-14 2019-11-05 西安电子科技大学 Based on radar signal direction-finding method, device and the computer storage medium improved under polar coordinate representation method model
CN110940976B (en) * 2019-11-18 2022-03-08 杭州电子科技大学 Error correction-based multi-station multi-external radiation source radar moving target positioning method
CN111239718B (en) * 2020-01-17 2022-11-15 电子科技大学 Multi-base-station target positioning method based on single-satellite radiation source
CN111983561A (en) * 2020-06-30 2020-11-24 江西锐迪航空科技发展有限公司 TDOA (time difference of arrival) positioning method for multiple unmanned aerial vehicle targets under receiver position error
CN113484854B (en) * 2021-07-21 2023-04-11 电子科技大学 Target positioning method with unknown external radiation source position

Family Cites Families (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
EP2865575B1 (en) * 2013-10-22 2022-08-24 Honda Research Institute Europe GmbH Confidence estimation for predictive driver assistance systems based on plausibility rules
CN104267375B (en) * 2014-10-08 2016-06-08 武汉大学 A kind of external illuminators-based radar net error self registration method
CN108196224B (en) * 2017-10-20 2023-07-25 郁涛 Method for realizing double-station passive positioning by using external radiation source with unknown position
CN108445445B (en) * 2018-02-06 2021-09-17 中国人民解放军战略支援部队信息工程大学 Distributed passive positioning method and device
CN108562892B (en) * 2018-04-09 2020-12-01 中国人民解放军海军航空大学 Unmanned aerial vehicle-mounted passive bistatic radar device and target positioning method
CN108717184B (en) * 2018-04-27 2020-09-01 杭州电子科技大学 Error correction-based DOA and TOA combined single-station passive positioning method
CN108387876B (en) * 2018-04-27 2020-11-27 杭州电子科技大学 External radiation source radar network double-base-distance error registration method based on CTLS

Also Published As

Publication number Publication date
CN109633591A (en) 2019-04-16

Similar Documents

Publication Publication Date Title
CN109633591B (en) External radiation source radar double-base-distance positioning method under observation station position error
CN109633592B (en) External radiation source radar time difference and frequency difference co-location method under motion observation station error
CN108717184B (en) Error correction-based DOA and TOA combined single-station passive positioning method
CN108387876B (en) External radiation source radar network double-base-distance error registration method based on CTLS
CN104950305B (en) A kind of real beam scanning radar angle super-resolution imaging method based on sparse constraint
CN110146848B (en) Frequency modulation continuous wave radar self-interference elimination method based on fractional order least mean square
CN101644760B (en) Rapid and robust method for detecting information source number suitable for high-resolution array
CN103605117B (en) Real-time phased array signal distortion correction method based on interference suppression
CN110888105B (en) DOA estimation method based on convolutional neural network and received signal strength
CN109324315A (en) Space-time adaptive based on double level block sparsity handles radar clutter suppression method
CN109375179A (en) A kind of strong clutter suppression method of airborne radar short range based on rarefaction representation
CN104898115A (en) Multi-target tracking method after through-wall radar imaging
CN110389327A (en) The more external illuminators-based radars of multistation are biradical away from localization method under receiving station&#39;s location error
CN115963457B (en) Multichannel passive radar direct wave interference suppression method
Kang et al. Adaptive complex‐EKF‐based DOA estimation for GPS spoofing detection
CN103852749A (en) Robust waveform optimization method for improving MIMO-STAP detection performance
CN116148829A (en) Multi-base radar positioning method based on non-cooperative external radiation source
Zhu et al. Low‐angle target tracking using frequency‐agile refined maximum likelihood algorithm
CN105044688A (en) Radar robust space-time adaption processing method based on iterative subspace tracking algorithm
Jiang et al. Underwater tdoa/fdoa joint localisation method based on cross‐ambiguity function
CN103954961A (en) Method for low-altitude obstacle super-resolution one-dimensional imaging of stepping frequency radar
Kwon et al. Particle filter based track-before-detect method in the range-doppler domain
Yang et al. Hybrid direct data domain sigma-delta space–time adaptive processing algorithm in non-homogeneous clutter
Lang et al. An efficient radon Fourier transform-based coherent integration method for target detection
CN107332601A (en) A kind of self-adapting interference suppression method based on wave beam forming

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