CN108061877A - A kind of passive track-corelation direction cross positioning method based on angle information - Google Patents
A kind of passive track-corelation direction cross positioning method based on angle information Download PDFInfo
- Publication number
- CN108061877A CN108061877A CN201711337488.7A CN201711337488A CN108061877A CN 108061877 A CN108061877 A CN 108061877A CN 201711337488 A CN201711337488 A CN 201711337488A CN 108061877 A CN108061877 A CN 108061877A
- Authority
- CN
- China
- Prior art keywords
- mrow
- msub
- msup
- data
- observation station
- 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.)
- Granted
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
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/0278—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves involving statistical or probabilistic considerations
-
- 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
- G01S5/00—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations
- G01S5/02—Position-fixing by co-ordinating two or more direction or position line determinations; Position-fixing by co-ordinating two or more distance determinations using radio waves
- G01S5/06—Position of source determined by co-ordinating a plurality of position lines defined by path-difference measurements
Landscapes
- Physics & Mathematics (AREA)
- Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Probability & Statistics with Applications (AREA)
- Position Fixing By Use Of Radio Waves (AREA)
Abstract
The invention belongs to electronic countermeasure technology fields, particularly relate to a kind of passive track-corelation direction cross positioning method based on angle information.The method of the present invention uses multi radiation sources data association algorithm first, the observation data of multiple observation stations are associated to obtain cost matrix C (p, q), further according to the cost matrix C (p of acquisition, q), using k averages ++ clustering algorithm estimates coordinates of targets.Beneficial effects of the present invention are that the present invention accurately can complete to associate to multistation data, and the final position for accurately estimating target, and method is simple, works well.
Description
Technical field
The invention belongs to electronic countermeasure technology fields, and it is more to particularly relate to a kind of passive multistation based on angle information
Bearing Cross Location Method.
Background technology
It is accurate to estimate that target emanation source position helps to obtain radiation source information during electronic reconnaissance, it is to carry out height
The key and Main Basiss of battle field situation and threat estimating on level and the important guarantee precisely hit realization of goal.
As electromagnetic environment constantly complicates, the requirement of positioning is also continuously improved, research of the domestic and foreign scholars to direction cross positioning
It is deepening continuously.In passive location system, what direction cross positioning was accompanied by electronic countermeasure activity and generated, be passive fixed
With a kind of most extensive, the longest localization method of search time in position.At present, track-corelation direction cross positioning faces as follows
Problem：1) when using multistation co-located, which how is distinguished in the measurement data of each passive station and is derived from same target
, and the measurement data for belonging to same target is combined and (completes measurement data association), it then could carry out target and determine
Position；It is present with false target if association is incorrect；2) with the increase of destination number, multiple passive observation stations can generate greatly
The false crosspoint of amount, how rejecting falseness crosspoint rapidly and efficiently.The problem of such so that the target numbers of acquisition
There are larger deviations between estimation and the estimation of position, it is therefore desirable to have new method, such issues that targetedly solve.
K- averages ++ algorithm is a kind of initial method for the clustering problem based on division, can efficiently solve on
The On The Choice of initial value is clustered, is improved k- mean algorithms.Know due to carrying out data clusters needs using k- mean algorithms
Road clusters number and initial cluster center point, and in a practical situation, it clusters number and initial cluster center point often cannot
Know in advance, so proposing k- averages ++ algorithm solve the problems, such as, on initial center, to have become one kind at present
The standard of hard clustering algorithm, but using k- averages ++ the research that clustering method be the clustering algorithm of representative in passive location at present and also
Seldom, it is to be worth the direction studied.
The content of the invention
In view of the above-mentioned problems, the present invention proposes a kind of combination multi radiation sources data correlation and k- averages ++ two kinds of calculations of cluster
Method realizes track-corelation direction cross positioning.
The technical solution adopted by the present invention is：
A kind of combination multi radiation sources data correlation and k- averages ++ what two kinds of algorithms of cluster positioned to realize track-corelation
Method, described is in using multistation direction cross positioning, is directed to false target and real goal crosspoint.Direction finding is handed over
Track-corelation location model is as shown in Figure 1 in fork method.
The coordinate of known observation station 1, observation station 2 and observation station 3 is respectively：(x1,y1)、(x2,y2)、(x3,y3), radiation source
1 and radiation source 2 coordinate it is unknown.Assuming that 3 observation stations observe that the azimuth of radiation source 1 is θ respectively1,1,θ2,1,θ3,1If spoke
The coordinate for penetrating source 1 is (xp,yq), then by formula：
The coordinate of radiation source 1 can be obtained, here niFor the angle measurement error of i-th of observation station.
But this is the orientation problem of single target, when multiple targets occurs in space, each observation station observes multiple
At this moment azimuth relates to each observation station Azimuthal Correlation problem, i.e. which azimuth is the same target of observation,
If data correlation mistake is just present with false target as shown in Figure 1, causes Wrong localization.In this case, it is of the invention
Using following methods：
A kind of passive track-corelation direction cross positioning method based on angle information, which is characterized in that including following
Step：
A, using multi radiation sources data association algorithm, the observation data of multiple observation stations is associated, are specifically included：
S1, assume that radiation source and observation station are all located on X/Y plane, it is known that the position coordinates (x of observation stationk,yk), k=1,
2 ... K, wherein K are observation station sums, and all observed azimuths for having measurement error in each observation station areWherein J is total radiation sources；
S2, the grid that objective plane is divided into P × Q scopes, each mesh point represent a position in objective plane and sit
Mark (xp,yq), wherein p=1,2 ..., P, q=1,2 ..., Q, each mesh point in grid plan is traveled through, calculates point (xp,yq)
Compared with the azimuth of each observation station：
Wherein：K=1,2 ... K, K are observation station sums；
S3, each Searching point (x is calculatedp,yq) compared with the azimuth angle alpha of observation stationk (p,q)It is observed with observation station
AzimuthBetween error ek (p,q)：
Wherein：K=1,2 ... K, j=1,2 ... J；
The cost matrix C (p, q) that S4, calculating are made of the overall error searched for every time：
Wherein：K=1,2 ... K, p=1,2 ..., P, q=1,2 ..., Q；
B, according to the cost matrix C (p, q) of acquisition, using k- averages ++ clustering algorithm estimates coordinates of targets, specific to wrap
It includes：
S6, data prediction：The data for being more than threshold value in cost matrix are rejected, remaining all data institute in a matrix
Corresponding index forms new data set X as element；
S7, new data set X as algorithm is inputted and is gathered, therefrom randomly choose a point x as in first cluster
The heart；
S8, for other each points in data set, calculate the distance D (x) of it and nearest cluster centre；
S9, selecting a new data point, the principle of selection is as new cluster centre：The corresponding point of larger D (x),
It is selected larger as the probability of cluster centre；
S10, repetition S7-S9 come until J cluster centre is selected, it is known that this J center is the estimated location of target.
Further, the specific method of the step S8 is：
S81, each distance D (x) for calculating, are stored in an array, then these distances are added up to obtain
sum(D(x))；
S82, a random value Random that can fall in sum (D (x)) is taken, as algorithm value sum (D (x)) * Random
When, which can be fallen into the larger sections of D (x) with larger probability, and the corresponding points of D (x) can be chosen with larger probability at this time
It is middle as new cluster centre.
Beneficial effects of the present invention are that the present invention accurately can complete to associate to multistation data, and finally accurately estimate
The position of target, method is simple, works well.
Description of the drawings
Fig. 1 is time difference locating technology illustraton of model；
Fig. 2 is multi radiation sources data association algorithm flow chart；
Fig. 3 is k- averages ++ algorithm flow chart
Fig. 4 is multiple target puppet spectral peak figure；
Fig. 5 is positioning result figure；
Fig. 6 is correct localization with threshold variation graph；
Fig. 7 is correct localization with range error change curve.
Specific embodiment
The present invention is described in detail with reference to embodiment：
Embodiment
This example verifies above-mentioned passive track-corelation direction cross positioning algorithm arrangement using matlab, for simplification
For the sake of, algorithm model is made the following assumptions：
1. all observation stations and target are all in X/Y plane；
2. all observation stations have identical direction finding precision；
3. all Engineering Errors are all added in angle measurement error；
4. assume that target is static or movement velocity is extremely low；
If target area is the square region of 200km × 200km, 6 radiation sources are distributed, coordinate is respectively：(135,
148.8), (173,191), (74.01,193.99), (84,131), (23,126.9), (119,59.71), unit km.It uses
3 fixed observer stations position above-mentioned target, and the coordinates of 3 observation stations is respectively (10,10), (100,30), (190,
10), unit km, the angle error of observation station obey the Gaussian Profile that average is zero, and between the angle error of 3 observation stations
Independently of each other.
Track-corelation data correlation effect：
As shown in figure 4, after the azimuth information on each target observed to multiple stations is associated, from figure
It can be seen that there is the pseudo- spectral peak figure of 6 targets, Fig. 4 is to prove that the data correlation of 6 targets is correct.
K- mean cluster effects：
K- mean clusters realize target positioning, angle error very it is small it is almost negligible under the premise of, carry out
1000 Monte Carlo emulation.
Due in observation process always there are measurement error, and error obey average be zero, the Gaussian Profile that variance is,
Therefore position should be distributed near actual position.Institute is right when the target finally obtained nearly reaches 100% according to correct localization
That answers is properly positioned thresholding, when obtaining the distance between target location and actual position less than thresholding, it is believed that obtained
Obtain correct positioning result.
More intuitively to show the locating effect of algorithm, Fig. 5 gives the locating effect of the 500th time.In figure, border circular areas
The correct localization region assert is represented, estimated location is located in border circular areas then identification and has been carried out correctly positioning, from
As can be seen that the algorithm can realize correct positioning in Fig. 5.
Meanwhile as seen from Figure 6, correct localization is gradually promoted with the increase of thresholding, when actual position and survey
Amount site error just have very high association accuracy when only having 5km it is possible thereby to definite one meet condition be properly positioned door
Limit.
Under conditions of thresholding is properly positioned, increase the angle error of observation station, angle error can be obtained to the algorithm
The influence of correct localization, as seen from Figure 7, when angle measurement error gradually increases, correct localization is also gradually reduced.Explanation
Error permission in the range of, direction finding interior extrapolation method joint k- averages ++ algorithm to realize track-corelation measurement data association and
It positions feasible.
Claims (2)
- A kind of 1. passive track-corelation direction cross positioning method based on angle information, which is characterized in that including following step Suddenly：A, using multi radiation sources data association algorithm, the observation data of multiple observation stations is associated, are specifically included：S1, assume that radiation source and observation station are all located on X/Y plane, it is known that the position coordinates (x of observation stationk,yk), k=1,2, ... K, wherein K are observation station sums, and all observed azimuths for having measurement error in each observation station areWherein J is total radiation sources；S2, the grid that objective plane is divided into P × Q scopes, each mesh point represent a position coordinates (x in objective planep, yq), wherein p=1,2 ..., P, q=1,2 ..., Q, each mesh point in grid plan is traveled through, calculates point (xp,yq) compared with The azimuth of each observation station：<mrow> <msup> <msub> <mi>&alpha;</mi> <mi>k</mi> </msub> <mrow> <mo>(</mo> <mi>p</mi> <mo>,</mo> <mi>q</mi> <mo>)</mo> </mrow> </msup> <mo>=</mo> <mi>a</mi> <mi>r</mi> <mi>c</mi> <mi>t</mi> <mi>a</mi> <mi>n</mi> <mfrac> <mrow> <msub> <mi>y</mi> <mi>q</mi> </msub> <mo>-</mo> <msub> <mi>y</mi> <mi>k</mi> </msub> </mrow> <mrow> <msub> <mi>x</mi> <mi>p</mi> </msub> <mo>-</mo> <msub> <mi>x</mi> <mi>k</mi> </msub> </mrow> </mfrac> <mo>;</mo> </mrow>S3, each Searching point (x is calculatedp,yq) compared with the azimuth angle alpha of observation stationk (p,q)The orientation observed with observation station AngleBetween error ek (p,q)：<mrow> <msup> <msub> <mi>e</mi> <mi>k</mi> </msub> <mrow> <mo>(</mo> <mi>p</mi> <mo>,</mo> <mi>q</mi> <mo>)</mo> </mrow> </msup> <mo>=</mo> <munder> <mrow> <mi>arg</mi> <mi>min</mi> </mrow> <mi>j</mi> </munder> <mrow> <mo>|</mo> <mrow> <msup> <msub> <mi>&alpha;</mi> <mi>k</mi> </msub> <mrow> <mo>(</mo> <mi>p</mi> <mo>,</mo> <mi>q</mi> <mo>)</mo> </mrow> </msup> <mo>-</mo> <msub> <mover> <mi>&theta;</mi> <mo>^</mo> </mover> <mrow> <mi>k</mi> <mo>,</mo> <mi>j</mi> </mrow> </msub> </mrow> <mo>|</mo> </mrow> <mo>;</mo> </mrow>The cost matrix C (p, q) that S4, calculating are made of the overall error searched for every time：<mrow> <mi>C</mi> <mrow> <mo>(</mo> <mi>p</mi> <mo>,</mo> <mi>q</mi> <mo>)</mo> </mrow> <mo>=</mo> <munderover> <mo>&Sigma;</mo> <mrow> <mi>k</mi> <mo>=</mo> <mn>1</mn> </mrow> <mi>K</mi> </munderover> <msup> <mrow> <mo>(</mo> <msup> <msub> <mi>e</mi> <mi>k</mi> </msub> <mrow> <mo>(</mo> <mi>p</mi> <mo>,</mo> <mi>q</mi> <mo>)</mo> </mrow> </msup> <mo>)</mo> </mrow> <mn>2</mn> </msup> <mo>;</mo> </mrow>B, according to the cost matrix C (p, q) of acquisition, using k- averages ++ clustering algorithm estimates coordinates of targets, specifically includes：S6, data prediction：The data for being more than threshold value in cost matrix are rejected, remaining all data are corresponding in a matrix Index as the new data set X of element composition；S7, new data set X as algorithm is inputted and is gathered, therefrom randomly choose a point x as first cluster centre；S8, for other each points in data set, calculate the distance D (x) of it and nearest cluster centre；S9, selecting a new data point, the principle of selection is as new cluster centre：The corresponding point of larger D (x), is chosen It is taken as larger for the probability of cluster centre；S10, repetition S7-S9 come until J cluster centre is selected, it is known that this J center is the estimated location of target.
- 2. a kind of passive track-corelation direction cross positioning method based on angle information according to claim 1, It is characterized in that, the specific method of the step S8 is：S81, each distance D (x) for calculating, are stored in an array, and then these distances are added up to obtain sum (D (x))；S82, a random value Random that can fall in sum (D (x)) is taken, it, should as algorithm value sum (D (x)) * Random Value can be fallen into the larger sections of D (x) with larger probability, at this time the corresponding points of D (x) can be selected using larger probability as New cluster centre.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711337488.7A CN108061877B (en) | 2017-12-14 | 2017-12-14 | A kind of passive track-corelation direction cross positioning method based on angle information |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201711337488.7A CN108061877B (en) | 2017-12-14 | 2017-12-14 | A kind of passive track-corelation direction cross positioning method based on angle information |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108061877A true CN108061877A (en) | 2018-05-22 |
| CN108061877B CN108061877B (en) | 2019-10-18 |
Family
ID=62138766
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201711337488.7A Active CN108061877B (en) | 2017-12-14 | 2017-12-14 | A kind of passive track-corelation direction cross positioning method based on angle information |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108061877B (en) |
Cited By (11)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108919211A (en) * | 2018-07-12 | 2018-11-30 | 中国船舶重工集团公司第七二四研究所 | A kind of positioning accuracy appraisal procedure towards three station co-locateds |
| CN109188417A (en) * | 2018-09-04 | 2019-01-11 | 同方电子科技有限公司 | The method that single station Passive Positioning is carried out to scan-type radiation source using unmanned aerial vehicle platform |
| CN110412504A (en) * | 2019-08-12 | 2019-11-05 | 电子科技大学 | It is associated with based on angle with the passive track-corelation of time difference information and localization method |
| RU2717231C1 (en) * | 2019-10-08 | 2020-03-19 | федеральное государственное казенное военное образовательное учреждение высшего образования "Военная академия связи имени Маршала Советского Союза С.М. Буденного" Министерства обороны Российской Федерации | Difference-ranging method of determining coordinates of a radio-frequency source |
| CN111079859A (en) * | 2019-12-31 | 2020-04-28 | 哈尔滨工程大学 | Passive multi-station multi-target direction finding cross positioning and false point removing method |
| CN111273228A (en) * | 2019-05-09 | 2020-06-12 | 哈尔滨工程大学 | Multi-coherent source positioning method based on traversal search strategy |
| CN111669698A (en) * | 2019-03-07 | 2020-09-15 | 广州慧睿思通信息科技有限公司 | Positioning method, device, system and storage medium |
| CN111999696A (en) * | 2020-08-02 | 2020-11-27 | 中国人民解放军海军工程大学 | Multi-platform direction-finding cross-positioning optimization method |
| CN113009414A (en) * | 2019-12-20 | 2021-06-22 | 中移(成都)信息通信科技有限公司 | Signal source position determining method and device, electronic equipment and computer storage medium |
| CN113390406A (en) * | 2021-06-16 | 2021-09-14 | 电子科技大学 | Multi-target data association and positioning method based on passive multi-sensor system |
| CN115524662A (en) * | 2022-10-27 | 2022-12-27 | 中国电子科技集团公司信息科学研究院 | Direction finding time difference combined positioning method and system, electronic equipment and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE10043055A1 (en) * | 2000-08-29 | 2002-03-14 | Univ Ilmenau Tech | Passive sound location involves forming direction-specific sound characteristics into stereo signal and analyzing it; binaural time differences are determined with cross-correlation technique |
| CN102156992A (en) * | 2011-04-14 | 2011-08-17 | 中国人民解放军海军航空工程学院 | Intelligent simulating method for passively locating and tracking multiple targets in two stations |
| CN103678949A (en) * | 2014-01-09 | 2014-03-26 | 江南大学 | Tracking measurement set partitioning method for multiple extended targets based on density analysis and spectrum clustering |
| CN106709662A (en) * | 2016-12-30 | 2017-05-24 | 山东鲁能软件技术有限公司 | Electrical equipment operation condition classification method |
| CN106802406A (en) * | 2017-01-17 | 2017-06-06 | 电子科技大学 | A kind of radiation source correlating method for passive radar |
-
2017
- 2017-12-14 CN CN201711337488.7A patent/CN108061877B/en active Active
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| DE10043055A1 (en) * | 2000-08-29 | 2002-03-14 | Univ Ilmenau Tech | Passive sound location involves forming direction-specific sound characteristics into stereo signal and analyzing it; binaural time differences are determined with cross-correlation technique |
| CN102156992A (en) * | 2011-04-14 | 2011-08-17 | 中国人民解放军海军航空工程学院 | Intelligent simulating method for passively locating and tracking multiple targets in two stations |
| CN103678949A (en) * | 2014-01-09 | 2014-03-26 | 江南大学 | Tracking measurement set partitioning method for multiple extended targets based on density analysis and spectrum clustering |
| CN106709662A (en) * | 2016-12-30 | 2017-05-24 | 山东鲁能软件技术有限公司 | Electrical equipment operation condition classification method |
| CN106802406A (en) * | 2017-01-17 | 2017-06-06 | 电子科技大学 | A kind of radiation source correlating method for passive radar |
Non-Patent Citations (1)
| Title |
|---|
| 孙鹏等: "测向交叉定位系统中的 K-means 聚类融合算法", 《电光与控制》 * |
Cited By (19)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN108919211B (en) * | 2018-07-12 | 2022-03-11 | 中国船舶重工集团公司第七二四研究所 | Positioning precision evaluation method oriented to three-station cooperative positioning |
| CN108919211A (en) * | 2018-07-12 | 2018-11-30 | 中国船舶重工集团公司第七二四研究所 | A kind of positioning accuracy appraisal procedure towards three station co-locateds |
| CN109188417A (en) * | 2018-09-04 | 2019-01-11 | 同方电子科技有限公司 | The method that single station Passive Positioning is carried out to scan-type radiation source using unmanned aerial vehicle platform |
| CN109188417B (en) * | 2018-09-04 | 2022-11-15 | 同方电子科技有限公司 | Method for single-station passive positioning of scanning radiation source by adopting unmanned aerial vehicle platform |
| CN111669698A (en) * | 2019-03-07 | 2020-09-15 | 广州慧睿思通信息科技有限公司 | Positioning method, device, system and storage medium |
| CN111669698B (en) * | 2019-03-07 | 2022-06-21 | 广州慧睿思通科技股份有限公司 | Positioning method, device, system and storage medium |
| CN111273228A (en) * | 2019-05-09 | 2020-06-12 | 哈尔滨工程大学 | Multi-coherent source positioning method based on traversal search strategy |
| CN110412504A (en) * | 2019-08-12 | 2019-11-05 | 电子科技大学 | It is associated with based on angle with the passive track-corelation of time difference information and localization method |
| RU2717231C1 (en) * | 2019-10-08 | 2020-03-19 | федеральное государственное казенное военное образовательное учреждение высшего образования "Военная академия связи имени Маршала Советского Союза С.М. Буденного" Министерства обороны Российской Федерации | Difference-ranging method of determining coordinates of a radio-frequency source |
| CN113009414B (en) * | 2019-12-20 | 2024-03-19 | 中移(成都)信息通信科技有限公司 | Signal source position determining method and device, electronic equipment and computer storage medium |
| CN113009414A (en) * | 2019-12-20 | 2021-06-22 | 中移(成都)信息通信科技有限公司 | Signal source position determining method and device, electronic equipment and computer storage medium |
| CN111079859B (en) * | 2019-12-31 | 2020-12-04 | 哈尔滨工程大学 | Passive multi-station multi-target direction finding cross positioning and false point removing method |
| CN111079859A (en) * | 2019-12-31 | 2020-04-28 | 哈尔滨工程大学 | Passive multi-station multi-target direction finding cross positioning and false point removing method |
| CN111999696A (en) * | 2020-08-02 | 2020-11-27 | 中国人民解放军海军工程大学 | Multi-platform direction-finding cross-positioning optimization method |
| CN111999696B (en) * | 2020-08-02 | 2023-07-04 | 中国人民解放军海军工程大学 | Multi-platform direction-finding cross positioning optimization method |
| CN113390406B (en) * | 2021-06-16 | 2022-05-24 | 电子科技大学 | Multi-target data association and positioning method based on passive multi-sensor system |
| CN113390406A (en) * | 2021-06-16 | 2021-09-14 | 电子科技大学 | Multi-target data association and positioning method based on passive multi-sensor system |
| CN115524662A (en) * | 2022-10-27 | 2022-12-27 | 中国电子科技集团公司信息科学研究院 | Direction finding time difference combined positioning method and system, electronic equipment and storage medium |
| CN115524662B (en) * | 2022-10-27 | 2023-09-19 | 中国电子科技集团公司信息科学研究院 | Direction finding time difference joint positioning method, system, electronic equipment and storage medium |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108061877B (en) | 2019-10-18 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN108061877B (en) | A kind of passive track-corelation direction cross positioning method based on angle information | |
| CN108089148B (en) | A kind of passive track-corelation direction cross positioning method based on time difference information | |
| CN111079859B (en) | Passive multi-station multi-target direction finding cross positioning and false point removing method | |
| CN108152789B (en) | Utilize the passive track-corelation data correlation and localization method of RSS information | |
| CN102707726B (en) | Target location method of unmanned plane | |
| CN107770859A (en) | A kind of TDOA AOA localization methods for considering base station location error | |
| Yu et al. | Geometry and motion-based positioning algorithms for mobile tracking in NLOS environments | |
| CN102325370A (en) | High-precision three-dimensional positioner for wireless sensor network node | |
| CN108061889A (en) | AIS and the correlating method of radar angular system deviation | |
| CN107621263A (en) | A kind of ground magnetic positioning method based on road magnetic signature | |
| CN108882149B (en) | NLOS compensation positioning method of distance correlation probability | |
| CN109946694A (en) | Circumference SAR multi-object tracking method based on stochastic finite collection | |
| CN106446422A (en) | Log likelihood estimation based novel passive locating and tracking method | |
| CN102288938B (en) | Effective three-dimensional positioning method for wireless sensor network node | |
| CN106934324A (en) | Based on the radar data correlating methods for simplifying many hypothesis algorithms | |
| CN110673090A (en) | Passive multi-station multi-target positioning method based on DBSCAN | |
| CN103826298A (en) | Wireless sensor network positioning and computing method for collaborative iterative optimization | |
| CN110412504A (en) | It is associated with based on angle with the passive track-corelation of time difference information and localization method | |
| CN107703482A (en) | The AOA localization methods that a kind of closed solutions are combined with iterative algorithm | |
| CN110531782A (en) | Unmanned aerial vehicle flight path paths planning method for community distribution | |
| CN101308206B (en) | Circumferential track mobile target tracking method under white noise background | |
| CN104793177A (en) | Microphone array direction finding method based on least square methods | |
| CN107607904A (en) | A kind of multiple target homogeneity recognition methods based on Angle Information | |
| CN103499809B (en) | A kind of Pure orientation double computer cooperation target following location path planing method | |
| CN107238835A (en) | A kind of anti-fork correlating method of formation target point boat |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |