【摘要】：相參捷變頻雷達(dá)具有優(yōu)異的低截獲、抗干擾和電磁兼容性能，研究其信號處理問題具有重要的應(yīng)用價值。論文主要考慮捷變頻雷達(dá)中多目標(biāo)距離速度聯(lián)合估計問題，圍繞在信號處理中如何利用觀測場景中稀疏信息的問題展開研究，取得了以下成果。 推導(dǎo)了捷變頻雷達(dá)脈沖回波的信號模型，將距離-速度聯(lián)合估計問題建模為線性方程組求解的問題，并說明該線性方程組是欠定的。采用傳統(tǒng)的匹配濾波處理欠定方程組，會出現(xiàn)嚴(yán)重的旁瓣平臺，造成虛警、小目標(biāo)被旁瓣掩蓋等問題。由于在同一個粗分辨單元內(nèi)目標(biāo)個數(shù)往往較少，捷變頻雷達(dá)觀測場景呈現(xiàn)出了明顯的稀疏性。壓縮感知算法通過挖掘場景的稀疏性這一先驗信息，能夠有效地求解該線性方程組，從而抑制旁瓣、準(zhǔn)確重建場景。 論證了壓縮感知算法在捷變頻雷達(dá)中的適用性。通過嚴(yán)格分析捷變頻雷達(dá)中觀測矩陣的性質(zhì)，定量地給出了關(guān)于場景稀疏度和雷達(dá)參數(shù)的充分條件。當(dāng)滿足該條件時，利用壓縮感知算法可在無噪聲的情況下精確重建稀疏場景，，或在有噪聲的情況下穩(wěn)健恢復(fù)場景。仿真和實測數(shù)據(jù)也驗證了壓縮感知算法在捷變頻雷達(dá)中距離-速度聯(lián)合估計中的有效性。 解決了壓縮感知算法中的模型失配問題。實際觀測場景通常是在距離速度連續(xù)二維空間上稀疏。將連續(xù)空間離散化時，場景中目標(biāo)可能并不在格點上，從而出現(xiàn)模型失配問題，導(dǎo)致傳統(tǒng)壓縮感知算法性能下降。提出了基于總體最小二乘的自適應(yīng)匹配追蹤算法來解決該失配問題。算法將格點誤差建模成未知參數(shù)，采用約束總體最小二乘算法自適應(yīng)地估計格點誤差，并利用估計結(jié)果相應(yīng)地調(diào)整觀測矩陣，降低模型失配的影響，從而提高場景估計的魯棒性。 將認(rèn)知機(jī)制引入捷變頻雷達(dá)中，利用已經(jīng)獲得的場景先驗信息，進(jìn)一步提高壓縮感知算法重建場景的精度。提出了最小化重建誤差的Cramer-Rao界(CRB)作為雷達(dá)脈沖載頻的優(yōu)化設(shè)計準(zhǔn)則，通過降低CRB使得雷達(dá)觀測系統(tǒng)能夠提供更多信息，降低不同目標(biāo)回波之間的相互干擾。論文還根據(jù)捷變頻雷達(dá)觀測矩陣的結(jié)構(gòu)特點，提出了最小化CRB的一種近似準(zhǔn)則，能夠有效地降低計算量。根據(jù)雷達(dá)不同的潛在需求，提出了序貫和批處理兩種優(yōu)化載頻的工作模式。
[Abstract]:Coherent frequency agile radar has excellent performance of low interception, anti-jamming and electromagnetic compatibility, so it has important application value to study the problem of signal processing. In this paper, the problem of joint range velocity estimation of multi-target in frequency-agility radar is considered. The problem of how to use sparse information in observation scene in signal processing is studied, and the following results are achieved. The signal model of pulse echo of agile frequency conversion radar is derived. The range velocity joint estimation problem is modeled as a linear equation system, and it is shown that the linear equation group is under determined. Using traditional matched filtering to deal with underdetermined equations will lead to serious sidelobe platform resulting in false alarm and small target being covered by sidelobe. Because of the small number of targets in the same coarse resolution unit, the observational scene of frequency agile radar shows obvious sparseness. By mining the prior information of scene sparsity, the compressed perceptual algorithm can solve the linear equations effectively, which can suppress the sidelobe and reconstruct the scene accurately. The applicability of compression sensing algorithm in frequency agility radar is demonstrated. By strictly analyzing the properties of observation matrix in frequency agility radar, the sufficient conditions about scene sparsity and radar parameters are given quantitatively. When this condition is satisfied the sparse scene can be accurately reconstructed without noise or the scene can be recovered stably in the presence of noise by using the compression sensing algorithm. The simulation and measured data also verify the effectiveness of the compression sensing algorithm in the range velocity joint estimation of frequency agility radar. The problem of model mismatch in compressed sensing algorithm is solved. The actual observation scene is usually sparse in the range velocity continuous two-dimensional space. When the continuous space is discretized, the target in the scene may not be on the lattice point, which leads to the model mismatch problem, which leads to the performance degradation of the traditional compression sensing algorithm. An adaptive matching tracking algorithm based on population least squares is proposed to solve the mismatch problem. The lattice error is modeled as an unknown parameter, and the constrained population least square algorithm is used to estimate the lattice error adaptively, and the observation matrix is adjusted accordingly using the estimation results to reduce the effect of model mismatch. In order to improve the robustness of scenario estimation. The cognitive mechanism is introduced into the frequency agility radar and the scene prior information obtained is used to further improve the accuracy of the compressed perceptual algorithm to reconstruct the scene. Cramer-Rao bound (CRB), which minimizes the reconstruction error, is proposed as the optimal design criterion for radar pulse carrier frequency. By reducing the CRB, the radar observation system can provide more information and reduce the mutual interference between the echoes of different targets. According to the structural characteristics of the observational matrix of frequency agile radar, an approximate criterion for minimizing CRB is proposed, which can effectively reduce the computational complexity. According to the different potential requirements of radar, two optimal carrier frequency operation modes, sequential and batch processing, are proposed.
【學(xué)位授予單位】：清華大學(xué)
【學(xué)位級別】：博士
【學(xué)位授予年份】：2014
【分類號】：TN957.51

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