【摘要】：天波超視距雷達(dá)(over-the-horizon radar,OTHR)中,機(jī)動(dòng)目標(biāo)信號(hào)存在頻譜擴(kuò)展,導(dǎo)致目標(biāo)檢測(cè)性能下降。強(qiáng)的海雜波進(jìn)一步增加了機(jī)動(dòng)目標(biāo)的檢測(cè)難度。針對(duì)該問(wèn)題,考慮到海雜波信號(hào)能量主要集中在零頻附近,而且可以建模為一個(gè)自回歸(auto-regressive,AR)過(guò)程,用AR濾波器抑制海雜波;考慮到機(jī)動(dòng)目標(biāo)信號(hào)近似為線性調(diào)頻信號(hào),而分?jǐn)?shù)階傅里葉變換(fractional Fourier transform,FRFT)能有效積累線性調(diào)頻信號(hào)的能量,因此采用FRFT算法估計(jì)目標(biāo)運(yùn)動(dòng)參數(shù),實(shí)現(xiàn)機(jī)動(dòng)目標(biāo)檢測(cè);在此基礎(chǔ)上用分級(jí)迭代的FRFT進(jìn)一步降低運(yùn)算量;針對(duì)多目標(biāo)檢測(cè)問(wèn)題,用"CLEAN"方法逐個(gè)檢測(cè)機(jī)動(dòng)目標(biāo)。仿真結(jié)果表明,與已有的離散多項(xiàng)式變換(discrete polynomial transform,DPT)算法相比,本文算法可以更好地適用于多目標(biāo)檢測(cè);與Radon-Wigner變換算法相比,本文算法可以達(dá)到更高的參數(shù)估計(jì)精度。
[Abstract]:In sky-wave over-the-horizon radar (over-the-horizon radar,OTHR), the spectrum spread of maneuvering target signal leads to the degradation of target detection performance. Strong sea clutter further increases the difficulty of maneuvering target detection. To solve this problem, considering that the energy of sea clutter is mainly concentrated near zero frequency, and can be modeled as an autoregressive (auto-regressive,AR) process, AR filter is used to suppress sea clutter. Considering that the maneuvering target signal is approximately linear frequency modulation (LFM) signal and fractional Fourier transform (fractional Fourier transform,FRFT) can effectively accumulate the energy of LFM signal, the moving parameters of maneuvering target are estimated by FRFT algorithm to realize maneuvering target detection. On this basis, the computational complexity is further reduced by using the hierarchical iterative FRFT, and the "CLEAN" method is used to detect the maneuvering targets one by one for the multi-target detection problem. The simulation results show that compared with the existing discrete polynomial transform (discrete polynomial transform,DPT) algorithm, the proposed algorithm is more suitable for multi-object detection, and the proposed algorithm can achieve higher parameter estimation accuracy than the Radon-Wigner transform algorithm.
【作者單位】： 電子科技大學(xué)電子工程學(xué)院;
【基金】：國(guó)家自然科學(xué)基金重點(diǎn)項(xiàng)目(61032010,61371184,61101172) 中央高校基本科研業(yè)務(wù)費(fèi)專項(xiàng)資金(ZYGX2012J018)資助課題
【分類號(hào)】：TN958.93

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