【摘要】：在現(xiàn)代電子戰(zhàn)中,線性調(diào)頻(LFM)信號因具有大帶寬與大時寬,在雷達目標探測中呈現(xiàn)出在距離與速度上的高分辨率性能。因此,能夠有效、高精度的實現(xiàn)線性調(diào)頻信號的參數(shù)估計對實現(xiàn)高精度目標探測意義重大。由于傳統(tǒng)的LFM信號參數(shù)估計算法精度較差已不能滿足現(xiàn)代雷達對高精度目標探測的要求,本文研究了能夠有效、精度更高的參數(shù)估計方法Radon-WDL變換(RWLT),其中WDL為Wigner-Ville分布與線性正則變換(LCT)結合的變換。同時,為了提高雷達目標探測的抗干擾性能,研究了針對于基于LFM信號的典型DRFM干擾—CI干擾與SMSP干擾的Radon-WDL變換參數(shù)估計方法。本文圍繞基于Radon-WDL變換的LFM信號、多分量LFM信號、CI干擾與SMSP干擾的參數(shù)估計問題進行了研究,主要研究內(nèi)容包含如下:1、針對有限長單分量LFM信號的參數(shù)估計精度問題,在Radon-WVD變換(RWT)基礎上,研究了Radon-WDL變換算法,其為對信號的WDL進行Radon直線積分。首先,研究了有限長單分量LFM信號的Radon-WDL變換的理論基礎及算法實現(xiàn)步驟。然后,通過蒙特卡洛仿真驗證:相對于Radon-WVD變換,Radon-WDL變換對有限長單分量LFM信號的參數(shù)估計的有效性與高精度性。2、針對多分量LFM信號參數(shù)估計中的交叉項干擾與參數(shù)估計的精度問題,在CLEAN-RWT變換的基礎上,研究了基于CLEAN-RWLT變換,其為“CLEAN”思想與RWLT相結合的變換。Radon-WDL變換不僅可以有效的抑制WDL變換的交叉項干擾,而且可以實現(xiàn)相對于傳統(tǒng)算法Radon-WVD變換更高精確的信號參數(shù)估計。“CLEAN”思想可以有效的消除遮掩影響以實現(xiàn)對多分量LFM信號進行逐個估計。最后,蒙特卡洛仿真驗證CLEAN-RWLT變換對多分量LFM信號參數(shù)估計的有效性與高精度性能。3、針對CI干擾與SMSP干擾的交叉項抑制與參數(shù)高精度識別問題,在Radon-WVD變換的基礎上,分別研究了針對于CI干擾與SMSP干擾的Radon-WDL變換算法。Radon-WDL變換不僅可以有效的抑制干擾WDL的交叉項,而且可以實現(xiàn)對于CI干擾與SMSP干擾的初始頻率與調(diào)頻斜率的有效的、更高精度參數(shù)估計。最后,蒙特卡洛仿真驗證了相對于Radon-WVD變換,Radon-WDL變換對CI干擾與SMSP干擾的參數(shù)估計的有效性與高精度性能。
[Abstract]:In modern electronic warfare, LFM (LFM) signals have high resolution performance in range and speed because of their large bandwidth and large time-width. Therefore, it is very important to realize the parameter estimation of LFM signal with high precision. Because the traditional parameter estimation algorithm of LFM signal has poor accuracy, it can not meet the requirements of modern radar for high precision target detection. In this paper, an effective and more accurate parameter estimation method, Radon-WDL transform (RWLT), is studied in this paper. Where WDL is the combination of Wigner-Ville distribution and linear regular transformation (LCT). At the same time, in order to improve the anti-jamming performance of radar target detection, the parameter estimation method of Radon-WDL transform for typical DRFM jammer CI jamming and SMSP jamming based on LFM signal is studied. In this paper, the parameter estimation of LFM signal, multi-component LFM signal, CI interference and SMSP interference based on Radon-WDL transform is studied. The main contents are as follows: 1. On the basis of Radon-WVD transform (RWT), the Radon-WDL transform algorithm is studied, which is the Radon line integral to the WDL of the signal. Firstly, the theoretical basis of Radon-WDL transform of finite length single component LFM signal and the steps of algorithm implementation are studied. Then, Monte Carlo simulation shows that compared with Radon-WVD transform, Radon-WDL transform is effective and accurate in parameter estimation of LFM signal with finite length and single component. In order to solve the problem of crossover interference and precision of parameter estimation in multicomponent LFM signal, based on CLEAN-RWT transform, CLEAN-RWLT transform is studied. It is a combination of "CLEAN" idea and RWLT. Radon-WDL transform can not only effectively suppress the cross-term interference of WDL transform, The method of "CLEAN" can eliminate the influence of masking and estimate the multi-component LFM signal one by one. Finally, Monte Carlo simulation verifies the validity and high accuracy of CLEAN-RWLT transform for multi-component LFM signal parameter estimation. 3. Aiming at the cross-term suppression of CI interference and SMSP interference and the high precision identification of parameters, based on Radon-WVD transform, The algorithms of Radon-WDL transform for CI interference and SMSP interference are studied respectively. Radon-WDL transform can not only effectively suppress the crossover of interference WDL, but also realize the initial frequency and frequency modulation slope of CI interference and SMSP interference. Higher precision parameter estimation. Finally, Monte-Carlo simulation verifies the validity and high accuracy of Radon-WDL transform in parameter estimation of CI interference and SMSP interference compared with Radon-WVD transform.
【學位授予單位】：電子科技大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TN911.23

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