CN109856629A - The parallel track initiation method of region rasterizing Multiple feature association based on Hough transformation - Google Patents
The parallel track initiation method of region rasterizing Multiple feature association based on Hough transformation Download PDFInfo
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- CN109856629A CN109856629A CN201910033693.7A CN201910033693A CN109856629A CN 109856629 A CN109856629 A CN 109856629A CN 201910033693 A CN201910033693 A CN 201910033693A CN 109856629 A CN109856629 A CN 109856629A
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Abstract
The parallel track initiation method of region rasterizing Multiple feature association based on Hough transformation that the present invention relates to a kind of, including: radar detection area is divided into multiple overlapped zonules according to distance, for each cell domain, set different reference cycle number (reference cycle number refers to number effective period for participating in ballot accumulation) and peak extraction thresholding, and can complete effectively to accumulate as condition to meet 95% expectation target, Hough transformation quantized interval is gone out using Monte Carlo simulation off-line calculation；Multiple regions are subjected to track initiation using the method for Hough transformation according to the parameter in respective region parallel simultaneously；Parallel processing is carried out this process of parameter space cumulant matrix will be traversed in each Hough transformation, parameter space cumulant matrix is divided by the identical submatrix of multiple sizes according to computing resource, each submatrix carries out parallel processing respectively.
Description
Technical field
The track initiation method based on Hough transformation that the present invention relates to a kind of.
Background technique
Track initiation, which refers to the process of, establishes track before not entering the track maintenance stage, be primarily asking for multiple target tracking
Topic, directly affects the performance of multiple target tracking.Common track initiation method can be divided into sequential processes method and batch processing
Two kinds of method.Hough transformation is as a kind of typical batch processing method, because it is to the insensitive, to random noise of local defect
Robustness and it is suitable for parallel processing, the in real time good characteristics such as application, it has also become the hot spot of current track initiation technique study.
The early 1980s, Smith and Winter for the first time introduce Hough transformation, as a kind of effective track
Initial mode.1994, Carlson, Evans and Wilson etc., from principle concept, accumulation method and starting effect isogonism
Degree, application of the detailed analysis based on the initial mode of Hough transformation in single search radar.1998, Yankowich was more
Hough transformation has been used in target multisensor track initiation blending algorithm.
Although many fruitful work have been made in forefathers, there is also all in a particular application for Hough transformation
More problems.Firstly, there is presently no a kind of choosing methods of generally acknowledged effective parameter space quantized interval；Secondly, as one
Kind batch processing method, the naturally occurring calculation amount of Hough transformation, the huge defect of amount of storage are necessarily required to consider in practical applications
Real time problems.
Summary of the invention
The purpose of the present invention is to provide a kind of, and the parallel track of region rasterizing Multiple feature association based on Hough transformation rises
Beginning method.
The technical solution for realizing the aim of the invention is as follows: first according to the maximum speed v of expectation targetmaxAnd scanning
The minimum range span DivDis=10*v in cycle T s computation partition regionmax* Ts is set in advance if calculated DivDis is less than
The minimum range span M set, then take DivDis=M.Search coverage in radar horizon R, which is divided into X span, is
DivDis+δdOverlapped zonule, δdIt is the distance of overlapping region,For each cell
Domain, according to observing environment reference cycle number Taging(reference cycle number refers to number effective period for participating in ballot accumulation) and peak
Value extracts thresholding Thr, goes out Hough transformation minimum quantization interval delta θ and Δ ρ according to target error in measurement off-line calculation respectively.By this
X region carries out track initiation using the method for Hough transformation according to the parameter in respective region parallel.
For the track initiation method itself based on Hough transformation, parallel processing is also carried out.By parameter space cumulant matrix
It is divided into N number of submatrix, N is determined by computing resource.Each submatrix individually creates task, and multiple submatrix parallel processings are appointed
The synchronously control of business is realized by the way of semaphore+message queue.
Compared with prior art, the present invention its remarkable advantage are as follows:
Entire search coverage is divided into multiple zonules by the present invention, uses different reference cycle numbers to different regions
TagingWith peak extraction thresholding Thr, quickly starting can be taken into account and inhibit false.It is miscellaneous due in entire radar observation region
Wave power is different, and the prior art all uses identical reference cycle number T in whole regionagingWith peak extraction thresholding Thr, if
Using higher TagingWith Thr, if then can not achieve quick starting in clutter region, according to lower TagingWith Thr,
It will lead to again in strong clutter region false too many.The partition method that the present invention uses uses high threshold in strong clutter region
To inhibit false, quickly starting is realized using low threshold in weak clutter region.Secondly, in the prior art, in entire detecting area
In domain, same group of quantized interval is taken to be handled.Since the error in measurement of radar target is observed in polar coordinate system,
It is transformed into rectangular coordinate system, it is big the small remote error range of short range error range necessarily occurs.The present invention is smaller in short range use
Quantized interval, remotely use larger quantization interval, be more in line with actual conditions.
The present invention has also carried out parallel processing to Hough transformation itself while multizone is parallel, can be more fully
Using computing resource, real-time is improved.Compared with prior art, more inputs be can handle in interval at the same time
Point mark, can also accomplish to handle in real time under strong clutter environment.
Detailed description of the invention
Fig. 1 parameter space cumulant matrix structure chart.
Fig. 2 submatrix parallel processing schematic diagram.
Specific embodiment
The parallel track initiation method of region rasterizing Multiple feature association based on Hough transformation is realized in accordance with the following steps.
(1) region division: according to the maximum speed v of expectation targetmaxAnd the minimum in scan period Ts computation partition region
Distance DivDis=10*vmax* Ts takes DivDis if calculated DivDis is less than preset minimum range span M
=M.It is DivDis+ δ that search coverage in radar horizon R, which is divided into X span,dOverlapped zonule, δdIt is
The distance of overlapping region,
(2) it determines the parameter in each region: determining reference cycle number T firstagingWith peak extraction thresholding Thr, if having
Prior information knows the power of the clutter in investigative range, is arranged by prior information；If no, according to the region T within 40kmaging
Region T within=8, Thr=7,40-80kmagingRegion T other than=6, Thr=5,80kmaging=4, Thr=3 are in this way
Mode value.Then according to taking fixed TagingAnd Thr, in conjunction with radar resolution, offline by the way of Monte Carlo simulation,
Calculate the quantized interval Δ θ and Δ ρ in each region.Δ θ and Δ ρ, which takes, is capable of forming 95% hope target effectively
The minimum quantization interval of accumulation.Here so-called formation effectively accumulation refers to TagingThe Targets Dots in a period can be in parameter space
There is Thr or more ballot in one or more quantifying units in cumulant matrix.
(3) parameter setting and initialization: according to the parameter in each region of parameter setting that step 2 determines.According to Δ θ by parameter
Spatial parameter θ ∈ (0 °, 180 °) is divided intoSection (for simplicity, 180) the quantized interval Δ θ of setting should be able to divide exactly,
According to Δ ρ by parameter space parameter ρ ∈ (rmin,rmax) be divided intoSection, establishes parameter space cumulant matrix The content that A and each of which elements A (i, j) are included is as shown in Figure 1, total throwing comprising the quantifying unit
Poll TotalVoteNum and a length are equal to reference cycle number TagingVote information fifo queueEach element Q of vote information queuekComprising corresponding history votes HisVoteNum (k),
Point mark array d (k)={ d (k, g) }G=1,2 ..., HisVoteNum (k).Total votes of quantifying unit are equal to quantifying unit ballot letter
The sum of queue all elements votes are ceased, i.e.,So far, initial work
It is fully completed, step below is alternately performed in each sector in sequence.
(4) Hough transformation ballot accumulation: all inputs in note current period region are DOT={ (x (doti), y
(doti))}Doti=1,2 ..., DotNum(the point mark sum that DotNum is current period).For arbitrary point mark (x (doti), y
(doti)), in conjunction with each θj=j* Δ θ, j=1,2 ..., N can be calculated
According to the i that each is calculated with its corresponding j, A (i, j) and A (i-1, j), A (i+1, j) these three quantifying units are enabled
Tail of the queue element Q in total votes TotalVoteNum and vote information queueTagingBallot value HisVoteNum
(Taging) add one, and the mark is recorded in QTagingPoint mark information array in.
(5) parameter space cumulant matrix is traversed: whenever sector triggering carrys out interim, traversal parameter space cumulant matrix.For
Each quantifying unit regards the unit if its ballot value is greater than Thr as local peaking.The quantization list come out for peak extraction
Member generates candidate track.The falseness in candidate track is rejected plus the method for observation error matrix using straight line fitting, will be rejected
Result afterwards is regarded as the quasi- track of current period, and there are in quasi- track group.For the step for, can be real using mode shown in Fig. 2
Existing N number of submatrix parallel processing, N are determined by computing resource.By taking powerpc board as an example, using semaphore combination message queue
Mode realizes the synchronously control of parallel task.The task of each parallel processing waits the same semaphore, by semflush letter
It counts while activating all N number of parallel tasks, realize the synchronization of task；It is past to disappear after each task completes the processing of itself
It ceases and sends a completion message in queue, continue waiting for semaphore；After all parallel tasks after the completion of message queue will receive N
Item completes message, carries out subsequent serial arithmetic again later.
(6) track duplicate removal and sector update: after the completion of parameter space cumulant matrix all traversal, repeating in quasi- track group
Track leave out, in quasi- track group remaining all tracks as initial results export.All initial results outputs of current period
Later, quasi- track group is emptied.For the either element A (i, j) in parameter space accumulation matrix A, by its vote information queue
Head of the queue element Q1Team out updates total votes TotalVoteNum=TotalVoteNum-HisVoteNum (1).Sequentially by Q2…
QTagingIt is assigned to Q1…QTaging-1, by tail of the queue element QTagingBallot value zero setting, point mark array empty.
Claims (2)
1. the parallel track initiation method of region rasterizing Multiple feature association based on Hough transformation, it is characterised in that:
S1: radar detection area is divided into according to distanceA span is DivDis+ δdOverlapped cell
Domain, wherein R is radar horizon, DivDis=max (10*vmax* Ts, M), vmax, Ts, M be respectively expectation target maximum
Speed, scan period and preset minimum range span, δdIt is the distance of overlapping region；
S2: for each cell domain, different reference cycle number T is setagingAnd peak extraction thresholding Thr, wherein referring to
Periodicity refers to number effective period for participating in ballot accumulation, and can complete effectively to accumulate with the expectation target of satisfaction 95% and be
Condition goes out Hough transformation quantized interval Δ θ and Δ ρ using Monte Carlo simulation off-line calculation；
S3: this X region is subjected to track initiation using the method for Hough transformation according to the parameter in respective region simultaneously.
2. the region rasterizing Multiple feature association parallel track initiation method according to claim 1 based on Hough transformation,
Located parallel it is characterized by: this process of parameter space cumulant matrix will be traversed in each Hough transformation in step s3
Reason: parameter space cumulant matrix is divided into the identical submatrix of N number of size, each submatrix creates an independent job order
It stays alone reason, N is determined by computing resource；Whenever sector triggering comes interim, while all N number of parallel tasks is activated, realize task
Synchronization；After each task completes the processing of itself, to message queue in send a completions message, wait swash next time
It is living；After all parallel tasks after the completion of message queue will receive N item complete message, carry out subsequent serial process again later.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113671482A (en) * | 2021-09-18 | 2021-11-19 | 哈尔滨工业大学 | Track initiation method based on multi-dimensional screening parallel Hough transformation |
Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070156286A1 (en) * | 2005-12-30 | 2007-07-05 | Irobot Corporation | Autonomous Mobile Robot |
| JP2011257204A (en) * | 2010-06-08 | 2011-12-22 | Kitakyushu Foundation For The Advancement Of Industry Science & Technology | Clutter suppression device and radar device |
| CN102540181A (en) * | 2011-12-26 | 2012-07-04 | 南京鹏力系统工程研究所 | Flight path initializing method based on trace point preprocessing of environmental information graph |
| CN103116160A (en) * | 2012-11-27 | 2013-05-22 | 电子科技大学 | Weak target detecting method based on random Hough transformation |
| CN105116398A (en) * | 2015-08-27 | 2015-12-02 | 南京航空航天大学 | Real time Hough transformation detection weak object method based on FPGA |
| CN107340514A (en) * | 2017-07-10 | 2017-11-10 | 中国人民解放军海军航空工程学院 | Hypersonic weak signal target RAE HT TBD integration detection methods in three dimensions |
| CN108490409A (en) * | 2018-03-06 | 2018-09-04 | 中国船舶重工集团公司第七二四研究所 | The automatic initial mode of three-dimensional radar based on flight path risk assessment |
-
2019
- 2019-01-11 CN CN201910033693.7A patent/CN109856629A/en active Pending
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070156286A1 (en) * | 2005-12-30 | 2007-07-05 | Irobot Corporation | Autonomous Mobile Robot |
| JP2011257204A (en) * | 2010-06-08 | 2011-12-22 | Kitakyushu Foundation For The Advancement Of Industry Science & Technology | Clutter suppression device and radar device |
| CN102540181A (en) * | 2011-12-26 | 2012-07-04 | 南京鹏力系统工程研究所 | Flight path initializing method based on trace point preprocessing of environmental information graph |
| CN103116160A (en) * | 2012-11-27 | 2013-05-22 | 电子科技大学 | Weak target detecting method based on random Hough transformation |
| CN105116398A (en) * | 2015-08-27 | 2015-12-02 | 南京航空航天大学 | Real time Hough transformation detection weak object method based on FPGA |
| CN107340514A (en) * | 2017-07-10 | 2017-11-10 | 中国人民解放军海军航空工程学院 | Hypersonic weak signal target RAE HT TBD integration detection methods in three dimensions |
| CN108490409A (en) * | 2018-03-06 | 2018-09-04 | 中国船舶重工集团公司第七二四研究所 | The automatic initial mode of three-dimensional radar based on flight path risk assessment |
Non-Patent Citations (5)
| Title |
|---|
| XIA DONG等: "A new Hough transform applied in track initiation", 《2011 INTERNATIONAL CONFERENCE ON CONSUMER ELECTRONICS, COMMUNICATIONS AND NETWORKS》 * |
| 夏栋等: "基于确定参数Hough变换的航迹起始", 《现代雷达》 * |
| 皇甫一江等: "基于霍夫变换的航迹起始方法研究", 《雷达与对抗》 * |
| 金术玲等: "两级Hough变换航迹起始算法", 《电子学报》 * |
| 鹿传国等: "并行Hough变换航迹起始", 《雷达学报》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113671482A (en) * | 2021-09-18 | 2021-11-19 | 哈尔滨工业大学 | Track initiation method based on multi-dimensional screening parallel Hough transformation |
| CN113671482B (en) * | 2021-09-18 | 2022-04-08 | 哈尔滨工业大学 | Track initiation method based on multi-dimensional screening parallel Hough transformation |
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Application publication date: 20190607 |