三維目標(biāo)曲線SAR成像的降維搜索算法
Dimension-Reduced Searching Method for 3-D Target Imaging in Curvilinear SAR
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摘要: 曲線合成孔徑雷達(dá)(CurviLinear Synthetic Aperture Radar，CLSAR)利用雷達(dá)平臺(tái)的單條曲線軌跡就可形成三維成像所需的曲線合成孔徑。由于CLSAR采集的數(shù)據(jù)在三維頻率空間是稀疏的，簡(jiǎn)單地采用非參數(shù)化方法所獲得的圖像幾乎無(wú)法使用，所以有價(jià)值的目標(biāo)三維像必須采用參數(shù)化方法來(lái)獲得。該文提出一種新的適用于CLSAR的目標(biāo)三維成像算法。該算法巧妙地利用了接收數(shù)據(jù)中距離方向與垂直距離方向參數(shù)間的弱耦合性，將高維優(yōu)化問(wèn)題解耦為低維優(yōu)化問(wèn)題，并順序地估計(jì)出相應(yīng)參數(shù)，最后采用一個(gè)迭代過(guò)程進(jìn)行參數(shù)求精。仿真實(shí)驗(yàn)表明，新算法是一種適用于CLSAR的有效的目標(biāo)三維成像算法。
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關(guān)鍵詞:
- 雷達(dá)信號(hào)處理;合成孔徑雷達(dá);雷達(dá)成像
Abstract: CurviLinear Synthetic Aperture Radar (CLSAR), whose aperture is formed via single curvilinear trajectory, has the capability of three-dimensional (3-D) imaging. The 3-D images obtained by using non-parametric methods, however, have little practical use because the data collected by CLSAR is sparse in 3-D frequency space. Valuable 3-D target images are obtained by parametric methods. In this paper, a new algorithm is proposed for imaging 3-D target in CLSAR. With smartly utilizing the loose coupling between the range and cross-range parameters, the new algorithm reduces the problem of high dimensional optimization into several lower dimensional optimization, estimates them in sequence, and refines them via iteration. Simulation results show the new algorithm can efficiently form the targets 3-D image via CLSAR. -
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