基于多普勒頻偏估計的單幀圖像低速運動目標(biāo)檢測方法

黃聰; 劉寅

doi:10.11999/JEIT151078

基于多普勒頻偏估計的單幀圖像低速運動目標(biāo)檢測方法

doi: 10.11999/JEIT151078

黃聰¹,
劉寅¹

基金項目:

國家重點實驗室基金(9140C200406110C2001)，國防基礎(chǔ)科研計劃(B2420132004)，國家863計劃項目 (2012AA 090901-4)

計量
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- 被引次數(shù): 0
出版歷程
- 收稿日期: 2015-09-21
- 修回日期: 2016-01-29
- 刊出日期: 2016-07-19

Low-speed Moving Target Detection of Single Frame Image Based on Doppler Shift Estimation

HUANG Cong¹,
LIU Yin¹

Funds:

The National Key Laboratory Foundation (9140C200406110C2001), The National Defense Basic Scientific Research Program of China (B2420132004), The National 863 Program of China (2012AA090901-4)

摘要

摘要: 常用的圖像域運動目標(biāo)檢測跟蹤方法對虛警率較敏感，當(dāng)虛警率較高時，目標(biāo)檢測跟蹤的實時性受限。為了降低目標(biāo)初始檢測的虛警率，進(jìn)而提高目標(biāo)檢測跟蹤的實時性，該文提出一種基于多普勒頻偏估計的單幀圖像低速運動目標(biāo)檢測算法，通過發(fā)射多普勒不敏感的LFM脈沖對，忽略多普勒效應(yīng)對成像結(jié)果的影響，但在圖像域檢測的同時，利用目標(biāo)回波的多普勒頻偏信息進(jìn)行靜目標(biāo)和雜波亮點的剔除，基于單幀數(shù)據(jù)，減小運動目標(biāo)檢測的虛警率，實現(xiàn)單幀圖像的運動目標(biāo)檢測，從而為目標(biāo)跟蹤奠定良好基礎(chǔ)。該算法首先進(jìn)行圖像域的恒虛警檢測，再利用寬帶時域波束形成和復(fù)相關(guān)頻率測量法，對檢測亮點處的波束輸出信號進(jìn)行多普勒測頻，僅通過單幀圖像就可有效剔除靜目標(biāo)和雜波亮點。同時為了改善寬帶時域波束形成的性能，利用2階錐規(guī)劃設(shè)計濾波器的系數(shù)，用9階FIR濾波器實現(xiàn)了0.01倍采樣點的小數(shù)時延，提高了多普勒頻偏的估計精度。最后通過計算機(jī)仿真和水池試驗驗證了所提算法的有效性。
- 2維成像 /
- 動目標(biāo)檢測 /
- 多普勒頻偏估計 /
- 小數(shù)時延
Abstract: The regular algorithms of target detection and tracking in image domain are very sensitive to the false alarm rate, and the real time performance of target detection and tracking is limited with high false alarm rate. In order to reduce the false alarm rate of original target detection and improve the real time performance, an algorithm of low-speed moving target detection of single frame image based on Doppler shift estimation is proposed. Through transmitting LFM plus pair signal which is non-sensitive to the Doppler shift, the influence on image by Doppler shift can be ignored. But during the detection in image domain, the Doppler shift of target echo is used to remove static targets and clutter highlights. The false alarm rate of moving target detection is reduced based on single frame data, the moving target detection is achieved through a single frame image to make a good foundation for target tracking later. First, the CFAR determination in image domain is carried out in the algorithm. Then, the Doppler shift of the beamforming signal at the highlights detected is estimated through time-domain broadband beamforming and complex correlation frequency measurement. The static targets and clutter highlights are removed effectively through single frame image. In order to improve the performance of time-domain broadband beamforming, the filter coefficients are designed by second order cone programming. The 0.01 times sampling point of the fractional delay is achieved by a 9-order FIR filter and the estimation accuracy of the Doppler shift is improved. The validity of the proposed method is verified by the computer simulation and pool experiment.
- Two-dimensional imaging /
- Moving target detection /
- Doppler shift estimation /
- Fractional delay

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