【摘要】：混響是主動聲納檢測的主要背景干擾,由于它是一種非平穩(wěn)的有色噪聲,使得工作在白噪聲條件下的檢測器性能受到極大限制。在混響背景下實現(xiàn)目標(biāo)回波檢測,常采用自回歸(AR)模型對寬帶回波預(yù)白化處理,但在強混響背景條件下,白化后直接進(jìn)行匹配濾波檢測的結(jié)果不甚理想。針對此問題,在AR模型預(yù)白化基礎(chǔ)上,提出一種改進(jìn)方法,對白化后信號先進(jìn)行二分奇異值分解(SVD)處理,有效去除大部分混響干擾,然后再作匹配檢測。仿真實驗分析表明,相比于僅白化后的匹配濾波檢測,該方法可提高信混比約3 d B,匹配檢測效果得到了明顯改善。
[Abstract]:Reverberation is the main background interference in active sonar detection. Because it is a non-stationary colored noise, the performance of detector working under white noise is greatly limited. In order to realize target echo detection in reverberation background, autoregressive (AR) model is often used to prewhiten wideband echo, but under strong reverberation background, the result of direct matched filtering detection after whitening is not satisfactory. In order to solve this problem, an improved method based on prewhitening of AR model is proposed. After whitening the signal is processed by binary singular value decomposition (SVD), most of the reverberation interference is removed effectively, and then matching detection is made. The simulation results show that compared with only whitened matched filter detection, this method can improve the signal-to-mixing ratio of about 3 dB, and the effect of matching detection is obviously improved.
【作者單位】： 海軍潛艇學(xué)院;
【基金】：國家高技術(shù)研究發(fā)展計劃(863計劃)項目~~
【分類號】：U666.7

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1 王靜;黃建國;張群飛;韓晶;;噪聲空間譜預(yù)白化小孔徑陣列被動目標(biāo)檢測方法[J];西北工業(yè)大學(xué)學(xué)報;2012年03期

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本文編號：2383936