CN111650624A - Data filtering method based on projection variance discrimination and implementation device thereof - Google Patents
Data filtering method based on projection variance discrimination and implementation device thereof Download PDFInfo
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- 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
- G01S19/00—Satellite radio beacon positioning systems; Determining position, velocity or attitude using signals transmitted by such systems
- G01S19/38—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system
- G01S19/39—Determining a navigation solution using signals transmitted by a satellite radio beacon positioning system the satellite radio beacon positioning system transmitting time-stamped messages, e.g. GPS [Global Positioning System], GLONASS [Global Orbiting Navigation Satellite System] or GALILEO
- G01S19/42—Determining position
Abstract
The invention provides a data filtering method based on projection variance discrimination and a realization device thereof, the method is provided according to the difference of the distribution variance of the measured moving target position data projected in different navigation directions, and comprises the following steps: generating projection bases of all possible navigation directions of the moving target; projecting the measured two-dimensional position data on each projection basis to realize dimension reduction; calculating the data variance after the position data projection, and taking the data variance as an estimated judgment condition; comparing the variances of all the projected data passing the course, selecting the projection base course with the largest variance as the course estimation of the moving target, and taking the projected target data as the preliminary estimation result of the flight path; and carrying out multipoint averaging on the preliminary estimation result, and taking the averaged track estimation result as a final output result.
Description
Technical Field
The invention relates to the technical field of data processing algorithms, in particular to a data filtering method based on projection variance judgment and an implementation device thereof.
Background
An Electronic Reconnaissance Satellite (Electronic Reconnaissance Satellite) is a Reconnaissance Satellite used to Reconnaissance, intercept electromagnetic signals emitted by enemy radar, communication and weapon telemetry systems, and measure the location of the source of the signal. The scouting satellite is only responsible for intercepting the original information of the enemy target limited by the computing power of the satellite, the original information is transmitted to the ground by the satellite, and the final information is completed by ground computing equipment.
The electronic reconnaissance satellite can be divided into a radar information reconnaissance satellite and a communication information reconnaissance satellite according to the difference of reconnaissance objects, and can be divided into fixed object reconnaissance and moving object reconnaissance according to the motion attribute of the reconnaissance object. The electronic reconnaissance satellite usually runs in an orbit of 300-500 km, and the interval of revisit reconnaissance to the same region is 1-3 hours. Multiple revisiting reconnaissance can be realized for a fixed target, and the reconnaissance quality is high; for a moving target, such as a marine ship, an aerial aircraft and the like, data of a single reconnaissance is required to be processed for realizing continuous repeated reconnaissance so as to obtain the position and the flight path of the moving target, so that the target position in the next revisit is effectively estimated, and prior knowledge is provided for the next reconnaissance to achieve the purpose of accurately intercepting target information.
Because the orbit of the electronic reconnaissance satellite is low, the coverage area of the electronic reconnaissance satellite on a ground fixed area is small, and the flying speed of the satellite relative to a ground moving target is high (the speed of the satellite is about 7.9 km/s, and the speed of a civil aircraft is about 0.25 km/s), the visual time of the electronic reconnaissance satellite on the ground target is about 10-20 minutes. Within the visible time of the electronic reconnaissance satellite, the running distance of the airplane (assuming constant-speed straight line navigation) is about 60 kilometers, and the running distance of the ship (assuming 25 sections of constant-speed straight line navigation) is about 10 kilometers. On the other hand, the electronic reconnaissance satellite is influenced by factors such as a technical system and measurement errors, and the measured signal source position has a random error of 5-10 kilometers. Fig. 1 is a schematic diagram showing a relationship between a conventional measurement position and a real position, wherein a five-pointed star indicates a real motion track of a moving object, and numbers indicate a sequence of track data; the square block indicates the measured position of the electronic reconnaissance satellite, and the number indicates the position of the measured position data point.
Disclosure of Invention
The invention aims to provide a data filtering method based on projection variance discrimination and an implementation device thereof, which are used for solving the problem of track filtering estimation of a moving target when a measured position error is equivalent to a track distance.
In order to solve the above technical problem, the present invention provides a data filtering method based on projection variance discrimination, where the data filtering method based on projection variance discrimination distributes variances on projection profiles at different speeds according to different measured position data of a moving object, and the method includes:
starting a data processing process when new original measurement position data enter the processing unit by adopting a data driving mode;
the data unit performs projection operation with all projection bases, the main direction after the projection operation is used as the sum of the data mean value and the variance, and the projection base with the largest variance and the projected data are selected;
calculating a course angle through the projection base with the maximum variance;
estimating confidence according to the course angle;
smoothing the projected data in a sliding window multipoint average mode to form a data sequence;
the data sequence is the final result of the data processing process of the processing module.
Optionally, in the data filtering method based on projection variance determination, the data filtering method based on projection variance determination further includes:
generating projection bases of all possible navigation directions of the moving target;
projecting the measured two-dimensional position data on each projection basis to realize dimension reduction;
calculating the data variance after the position data projection, and taking the data variance as an estimated judgment condition;
comparing the variances of all the projected data passing the course, selecting the projection base course with the largest variance as the course estimation of the moving target, and taking the projected target data as the preliminary estimation result of the flight path;
and performing multipoint averaging on the preliminary estimation result, and taking the averaged track estimation result as a final output result to finish the dynamic estimation of the target track of the electronic reconnaissance satellite.
Optionally, in the data filtering method based on projection variance determination, the data is processed according to a two-dimensional variance statistical characteristic of the moving target measurement position data on the ground.
Optionally, in the data filtering method based on projection variance discrimination, the projection bases of all possible navigation directions of the moving object are obtained by pre-calculation according to the requirement of course precision.
Optionally, in the data filtering method based on projection variance determination, the final heading of the moving target is obtained by calculating the most likelihood degree of the statistical characteristics of the measured data in different directions in a preset navigation.
Optionally, in the data filtering method based on projection variance determination, the reducing the dimension of the two-dimensional data includes reducing the dimension of the two-dimensional data by projecting the measurement data of the moving object onto a preset projection base direction.
The invention also provides a device for realizing the data filtering method based on the projection variance discrimination, which comprises the following steps:
the processor is used for interface processing of input signals, core algorithm realization and interface processing of output signals;
a memory; and
the peripheral configuration is that the peripheral configuration is,
wherein the processor is configured to perform the method of any one of claims 1 to 6.
Optionally, in the implementation apparatus of the data filtering method based on projection variance discrimination, the processor is an FPGA/CPLD, a DSP, or an MCU.
Optionally, in the implementation apparatus of the data filtering method based on the projection variance determination, the memory is an SRAM.
Optionally, in the implementation apparatus of the data filtering method based on projection variance determination, the core algorithm is implemented by a processor implementing serial-to-parallel conversion of input data, instantiation of a multiplier, calculation of a mean and a variance, and format coding conversion of output data through a program.
In the data filtering method and the implementation device thereof based on the projection variance discrimination, a data processing method based on the projection variance discrimination is provided according to the difference of the distribution variance of the measured position data of the moving target on the projection in different moving directions, the measured position data is projected on projection bases in all directions, then the mean variance after projection is calculated, and the projection base with the largest variance is taken as the estimated value of the course; meanwhile, a device for realizing the algorithm is provided based on the estimation algorithm. The electronic reconnaissance satellite target track dynamic estimation method based on the invention can better solve the track filtering estimation problem of the moving target when the measured position error is equivalent to the target movement distance, thereby estimating the course of the moving target in the original measured position error data.
Drawings
Fig. 1 shows a diagram 100 of the relationship between the measurement position of a survey satellite measuring an object and the true position of the object in the prior art.
Fig. 2 shows an algorithmic schematic 200 of a method for dynamically estimating a target trajectory of an electronic reconnaissance satellite according to an embodiment of the present invention.
Fig. 3 shows a schematic diagram 300 of an implementation apparatus of a method for dynamically estimating a target track of an electronic reconnaissance satellite according to an embodiment of the present invention.
Fig. 4 is a flowchart illustrating an implementation apparatus of a method for dynamically estimating a target track of an electronic reconnaissance satellite according to an embodiment of the present invention.
Fig. 5 is a schematic diagram illustrating an actual processing result of a method for dynamically estimating a target track of an electronic reconnaissance satellite according to an embodiment of the present invention.
Detailed Description
In the following description, the invention is described with reference to various embodiments. One skilled in the relevant art will recognize, however, that the embodiments may be practiced without one or more of the specific details, or with other alternative and/or additional methods, materials, or components. In other instances, well-known structures, materials, or operations are not shown or described in detail to avoid obscuring aspects of embodiments of the invention. Similarly, for purposes of explanation, specific numbers, materials and configurations are set forth in order to provide a thorough understanding of the embodiments of the invention. However, the invention may be practiced without specific details. Further, it should be understood that the embodiments shown in the figures are illustrative representations and are not necessarily drawn to scale.
Reference in the specification to "one embodiment" or "the embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment is included in at least one embodiment of the invention. The appearances of the phrase "in one embodiment" in various places in the specification are not necessarily all referring to the same embodiment.
It should be noted that, in the embodiments of the present invention, the process steps are described in a specific order, however, this is only for convenience of distinguishing the steps, and the order of the steps is not limited, and in different embodiments of the present invention, the order of the steps may be adjusted according to the adjustment of the process.
The invention provides a dynamic estimation method of an electronic reconnaissance satellite target track and an implementation device thereof. According to the difference of distribution variances of measured position data of a moving target on projections in different moving directions, a data processing method based on projection variance judgment is provided, the measured position data are projected onto projection bases in all directions, then the mean variance after projection is calculated, and the projection base with the largest variance is taken as an estimated value of a course; meanwhile, a device for realizing the algorithm is provided based on the estimation algorithm. The electronic reconnaissance satellite target track dynamic estimation method based on the invention can better solve the track filtering estimation problem of the moving target when the measured position error is equivalent to the target movement distance, thereby estimating the course of the moving target in the original measured position error data.
The electronic reconnaissance satellite target track dynamic estimation method adopts a processing method aiming at the motion target track estimation. Firstly, filtering data according to the two-dimensional variance statistical characteristic of the moving target measurement position data on the ground; then, pre-designing projection bases of all possible motion directions of the moving target, not directly calculating the course from data, but judging the most likelihood degree of the preset navigation through data characteristics; secondly, reducing the dimension of the two-dimensional data in a mode of projecting the measurement data of the moving target to a preset projection base direction, and then calculating the variance of the target data after dimension reduction to be used as a judgment condition of the most likelihood estimation; then, by comparing all data variances projected by preset courses, selecting the projection base course with the largest variance as course estimation of the moving target, and taking the projected target data as the preliminary estimation result of the flight path; and finally, carrying out variance multipoint averaging on the preliminary estimation result, and taking the averaged track estimation result as the final output result of the method.
The electronic reconnaissance satellite target track dynamic estimation method provided by the invention adopts a dynamic mode by adopting a processing method aiming at the motion target track estimation. And the final output result is iterated step by step along with the continuous increase of the input data, the algorithm is iterated and updated once every new original measurement enters the algorithm, meanwhile, the algorithm divides the variance of the course projection base and the variance of the projection base perpendicular to the course, and the divided result is used as the confidence coefficient of the algorithm for course estimation.
The principle of a method for dynamically estimating the trajectory of an electronic reconnaissance satellite target according to an embodiment of the present invention will be described in detail with reference to fig. 2. Fig. 2 shows an algorithmic schematic 200 of a method for dynamically estimating a target trajectory of an electronic reconnaissance satellite according to an embodiment of the present invention.
As shown in FIG. 2, a preset projection basis r is first generatedn＝[a b]The scale and the fineness of the projection base can be set according to the requirements of actual use scenes, the heading phi covered by the projection base ranges from 0 to 360 degrees, and phi is tan (b/a), and the generated projection base is stored in a memory in advance. The whole algorithm processing unit adopts a data driving mode, and once new data enter the processing unit, a data processing process is started.
After the original measurement position data arrives, new data enters a buffer memory, and then is arranged into a packet of data unit x [ x ] with the data buffered before (only the new data if the data is the first data, and no buffer data)1x2x3…]T. The data unit and all projection bases perform projection operation xTrnTaking the mean value mu of data in the main direction after projection operationnAnd ∑ n of the variance, and selecting the projection base r with the largest variancenAnd the projected data Y ═ xTrn。
And calculating a heading angle phi (arctan (b/a)) through the projection base. Heading angle estimation confidence
＝1-(∑n，min/∑n，max)。
Smoothing the projected data Y in a sliding window multipoint averaging mode, wherein the specific method comprises the following steps:
Zm＝∑(y(m-1)n+1,y(m-1)n+2,…,y(m-1)n+n)and/n, wherein the data sequence Z is the final result of the algorithm processing module.
An implementation apparatus and a working process of a method for dynamically estimating a target track of an electronic reconnaissance satellite according to an embodiment of the present invention are described in detail below with reference to fig. 3 and 4. Fig. 3 shows a schematic diagram 300 of an implementation apparatus of a method for dynamically estimating a target track of an electronic reconnaissance satellite according to an embodiment of the present invention, as shown in fig. 3, the implementation apparatus of the method for dynamically estimating a target track of an electronic reconnaissance satellite includes an implementation apparatus composed of a processor, a memory, and a peripheral configuration, where the processor may be an FPGA/CPLD, a DSP, or an MCU, and the processor is a specific implementation carrier of estimation of the present invention and is divided into an interface process of an input signal, a core algorithm implementation part, and an interface process of an output signal. The generation of a projection base, projection calculation, mean calculation, variance calculation, a comparator, confidence coefficient, a selector and a track estimation algorithm are realized through a preset algorithm.
In one embodiment of the invention, an FPGA is used for implementation. The FPGA realizes the algorithm in the content of the invention through a program, and the algorithm comprises serial-parallel conversion of input data, instantiation of a multiplier, calculation of mean value and variance and format coding conversion of output data. The mean calculation and the variance calculation are realized by an accumulator and a multiplier. In one embodiment of the invention, the precision of the projection vector is 0.1 °, and 3600 projection bases are formed together; the corresponding need generates 3600 multipliers for projection calculations. After new input data enter, the FPGA copies 3600 parts of the input data, the input data are respectively sent to a multiplier of projection calculation to be multiplied with the registered projection basis, and the projection result is put into a mean value/variance calculation buffer. The cache also comprises the cache results calculated before in addition to the projection results calculated latest, and after the new projection calculation results arrive, the average and variance calculation is driven once again, so that 3600 average and variance calculation results are generated. 3600 variance calculation results calculate the maximum value as the estimated direction of the data, and the projection base calculation course angle phi is the arctan (b/a) is completed by the coefficient of the maximum variance projection base by using CORDIC nuclear calculation.
Fig. 4 shows a working flow chart of an implementation apparatus for a method for dynamically estimating a target track of an electronic reconnaissance satellite according to an embodiment of the present invention, as shown in fig. 4, an image file of an implementation apparatus FPGA is stored in an EEPROM, after the apparatus is powered on, first, initialization of each hardware of the apparatus is performed, wherein after the initialization is completed, calculation of a projection vector is performed, and a projection basis coefficient that is completed by the calculation is stored in an SRAM. And after the projection base calculation and storage are finished, the device formally enters a data calculation flow. And the FPGA reads the projection base coefficient stored in the SRAM once.
Fig. 5 is a schematic diagram illustrating an actual processing result of a method for dynamically estimating a target track of an electronic reconnaissance satellite according to an embodiment of the present invention. As shown in fig. 5, the effect of treatment was observed for a certain experiment (1000 times total). The square is a simulated measuring position point, the circle is a simulated real position of the moving target, and the left triangle is a result processed by the text algorithm. In the experiment, 300 positions are simulated together, the heading is 45 degrees (45 degrees east to north), the speed is 14 knots, and the time interval of the simulated position points is 4 seconds. The average position error of 1000 times of 300 position points in the experiment is 526m, and the standard deviation of distribution is 63 m; the mean error of the heading angle was 2.6 degrees and the standard deviation of the distribution was 24.1 degrees.
The invention provides a dynamic estimation method for a target track of an electronic reconnaissance satellite and an implementation device thereof. According to the difference of distribution variances of measured position data of a moving target on projections in different moving directions, a data filtering method based on projection variance judgment is provided, the measured position data are projected onto projection bases in all directions, then the mean variance after projection is calculated, and the projection base with the largest variance is taken as an estimated value of a course; meanwhile, a device for realizing the algorithm is provided based on the estimation algorithm. The electronic reconnaissance satellite target track dynamic estimation method based on the invention can better solve the track filtering estimation problem of the moving target when the measured position error is equivalent to the target movement distance, thereby estimating the course of the moving target in the original measured position error data. Has the following advantages: 1) the method is novel, abandons the analytic calculation mode of calculating the course from data, adopts a statistical method to calculate the variance of the measured position data on different courses on a two-dimensional plane to estimate the course, and is easy to realize engineering. 2) The parallelization degree is high, the measured position data are projected to each projection base by pre-calculating the projection base in each direction, and then the mean variance after each projection is calculated. The designed algorithm has a parallel structure, is easy to realize on hardware such as FPGA and the like, and realizes the quick calculation of the algorithm. 3) Simple structure and low complexity.
While various embodiments of the present invention have been described above, it should be understood that they have been presented by way of example only, and not limitation. It will be apparent to persons skilled in the relevant art that various combinations, modifications, and changes can be made thereto without departing from the spirit and scope of the invention. Thus, the breadth and scope of the present invention disclosed herein should not be limited by any of the above-described exemplary embodiments, but should be defined only in accordance with the following claims and their equivalents.
Claims (10)
1. A data filtering method based on projection variance discrimination is characterized in that the data filtering method based on projection variance discrimination distributes variance on projection sections with different speeds according to the difference of measured position data of a moving object, and comprises the following steps:
starting a data processing process when new original measurement position data enter the processing unit by adopting a data driving mode;
the data unit performs projection operation with all projection bases, the main direction after the projection operation is used as the sum of the data mean value and the variance, and the projection base with the largest variance and the projected data are selected;
calculating a course angle through the projection base with the maximum variance;
estimating confidence according to the course angle;
smoothing the projected data in a sliding window multipoint average mode to form a data sequence;
the data sequence is the final result of the data processing process of the processing module.
2. The method for filtering data based on projection variance discrimination as claimed in claim 1, wherein the method for filtering data based on projection variance discrimination further comprises:
generating projection bases of all possible navigation directions of the moving target;
projecting the measured two-dimensional position data on each projection basis to realize dimension reduction;
calculating the data variance after the position data projection, and taking the data variance as an estimated judgment condition;
comparing the variances of all the projected data passing the course, selecting the projection base course with the largest variance as the course estimation of the moving target, and taking the projected target data as the preliminary estimation result of the flight path;
and performing multipoint averaging on the preliminary estimation result, and taking the averaged track estimation result as a final output result to finish the dynamic estimation of the target track of the electronic reconnaissance satellite.
3. The method of claim 2 further comprising processing the data based on two-dimensional variance statistics of the measured position data of the moving object over the ground.
4. The data filtering method based on the projection variance discrimination as claimed in claim 2, wherein the projection bases of all possible navigation directions of the moving object are pre-calculated according to the heading accuracy requirement.
5. The data filtering method based on the projection variance discrimination as claimed in claim 2, wherein the final heading of the moving object is obtained by calculating the most likelihood degree of the statistical characteristics of the measured data in different directions in a preset navigation.
6. The method of claim 2, wherein the reducing the dimension of the two-dimensional data comprises reducing the dimension of the two-dimensional data by projecting the measurement data of the moving object in a predetermined projection base direction.
7. An implementation apparatus for a data filtering method based on projection variance discrimination is characterized by comprising:
the processor is used for interface processing of input signals, core algorithm realization and interface processing of output signals;
a memory; and
the peripheral configuration is that the peripheral configuration is,
wherein the processor is configured to perform the method of any one of claims 1 to 6.
8. The apparatus for implementing a data filtering method based on projection variance estimation as claimed in claim 7, wherein the processor is FPGA/CPLD, DSP or MCU.
9. The apparatus for implementing a data filtering method based on projection variance estimation as claimed in claim 7, wherein the memory is an SRAM.
10. The apparatus for implementing data filtering method based on projection variance discrimination as claimed in claim 7, wherein the core algorithm is implemented by a processor through a program to implement serial-to-parallel conversion of input data, instantiation of a multiplier, calculation of mean and variance, and format coding conversion of output data.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103247057A (en) * | 2013-05-08 | 2013-08-14 | 西北工业大学 | Road target multi-hypothesis tracking algorithm under target-echo-road network data association |
| CN104743141A (en) * | 2015-04-03 | 2015-07-01 | 上海微小卫星工程中心 | High-speed aircraft positioning method with satellite constellation |
| CN104881521A (en) * | 2015-05-05 | 2015-09-02 | 电子科技大学 | Label random-set filter distribution type fusion method |
| CN105223583A (en) * | 2015-09-10 | 2016-01-06 | 清华大学 | A kind of target vehicle course angle computing method based on three-dimensional laser radar |
| CN106568442A (en) * | 2016-10-18 | 2017-04-19 | 中冶华天南京电气工程技术有限公司 | Synergetic navigation wave filtering method having robust characteristic |
| CN107132563A (en) * | 2017-07-10 | 2017-09-05 | 北京理工大学 | A kind of odometer combination double antenna difference GNSS Combinated navigation method |
| CN108548535A (en) * | 2018-03-13 | 2018-09-18 | 杨勇 | The initial method of low speed GNSS/MEMS integrated navigation systems |
Family Cites Families (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101776763B (en) * | 2010-01-19 | 2012-10-31 | 中国民航大学 | Self-coherent MUSIC algorithm-based global positioning system interference suppressing method |
| CN104166136A (en) * | 2014-07-11 | 2014-11-26 | 河海大学 | Interference subspace tracking-based high-efficiency self-adaptive monopulse angle measurement method |
| CN106055885B (en) * | 2016-05-26 | 2018-12-11 | 哈尔滨工业大学 | Unmanned plane during flying data exception detection method is tracked based on over-sampling projection approximation base |
| CN108415040B (en) * | 2018-03-15 | 2021-11-09 | 沈阳航空航天大学 | CSMG beam forming method based on subspace projection |
-
2018
- 2018-09-29 CN CN202010542561.XA patent/CN111650624B/en active Active
- 2018-09-29 CN CN201811148622.3A patent/CN109163727B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103247057A (en) * | 2013-05-08 | 2013-08-14 | 西北工业大学 | Road target multi-hypothesis tracking algorithm under target-echo-road network data association |
| CN104743141A (en) * | 2015-04-03 | 2015-07-01 | 上海微小卫星工程中心 | High-speed aircraft positioning method with satellite constellation |
| CN104881521A (en) * | 2015-05-05 | 2015-09-02 | 电子科技大学 | Label random-set filter distribution type fusion method |
| CN105223583A (en) * | 2015-09-10 | 2016-01-06 | 清华大学 | A kind of target vehicle course angle computing method based on three-dimensional laser radar |
| CN106568442A (en) * | 2016-10-18 | 2017-04-19 | 中冶华天南京电气工程技术有限公司 | Synergetic navigation wave filtering method having robust characteristic |
| CN107132563A (en) * | 2017-07-10 | 2017-09-05 | 北京理工大学 | A kind of odometer combination double antenna difference GNSS Combinated navigation method |
| CN108548535A (en) * | 2018-03-13 | 2018-09-18 | 杨勇 | The initial method of low speed GNSS/MEMS integrated navigation systems |
Non-Patent Citations (4)
| Title |
|---|
| 刘家祥: "航天电子侦察定位技术理论研究与仿真软件设计", 《中国优秀博硕士学位论文全文数据库(硕士)工程科技Ⅱ辑》 * |
| 胡耀武: "重力_惯性组合导航算法研究", 《中国优秀博硕士学位论文全文数据库(硕士)信息科技辑》 * |
| 范恩: "基于模糊信息处理的传感网系统中多目标跟踪方法", 《中国优秀博硕士学位论文全文数据库(博士)信息科技辑》 * |
| 马菁涛 等: "一种用于密集强弱目标速度高分辨估计的 IAA-MCapon 算法", 《电子学报》 * |
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