本文選題：機動目標 + 參數(shù)估計��； 參考：《中國民航大學》2015年碩士論文

【摘要】：機動目標回波信號的多普勒頻率在相干處理時間(Coherent Processing Interval,CPI)內(nèi)隨時間發(fā)生變化,即發(fā)生多普勒走動,使得傳統(tǒng)的空時自適應處理(Space-Time Adaptive Processing,STAP)算法相參積累性能降低,導致機動目標檢測與參數(shù)估計能力下降。當機動目標的加速度恒定時,其回波信號可視為線性調(diào)頻(Linear Frequency Modulation,LFM)信號。而采用時頻分析方法對加速度恒定的機動目標進行檢測和參數(shù)估計時需要的脈沖數(shù)較多,否則參數(shù)估計精度難以滿足要求。機載雷達在一個CPI內(nèi)發(fā)射的脈沖數(shù)相對較少,當脈沖重復頻率一定時,脈沖數(shù)較少意味著相干處理時間變短。因此,很難將時頻分析方法直接應用到短相干處理時間情況下機載雷達的機動目標檢測與參數(shù)估計的研究中。針對上述問題,本論文提出的機動目標檢測與參數(shù)估計方法在短相干處理時間情況下能夠獲得較高的參數(shù)估計精度。論文的主要貢獻和創(chuàng)新之處主要有:第一,介紹了機載雷達接收的回波數(shù)據(jù)模型,通過對多普勒問題的描述推導出機動目標的回波數(shù)據(jù)模型;第二,提出了一種基于重構(gòu)信號和時間采樣的機動目標檢測與參數(shù)估計方法,該方法在短相干處理時間情況下仍然可以獲得較好的機動目標參數(shù)估計結(jié)果,參數(shù)估計性能更加接近Cramer-Rao下界。第三,提出了一種基于壓縮感知和三次相位變換(Cubic Phase Transform,CPT)的低復雜度機動目標參數(shù)估計方法,可用小于Nyquist采樣定理要求的采樣頻率對信號進行采樣和壓縮。在短相干處理時間情況下,該方法不僅能夠獲得準確的機動目標參數(shù)估計結(jié)果,而且運算復雜度較低。第四,推導出機動目標參數(shù)估計的Cramer-Rao下界,為驗證本論文提出算法的有效性提供了理論依據(jù)。
[Abstract]:The Doppler frequency of maneuvering target echo signal changes with time in coherent processing time and coherent processing (CPI), that is, Doppler migration occurs, which makes the coherent accumulation performance of traditional space-time adaptive processing Space-Time Adaptive processing STAP algorithm decrease. The ability of maneuvering target detection and parameter estimation is reduced. When the acceleration of maneuvering target is constant, the echo signal can be regarded as linear frequency modulation LFM signal. The time-frequency analysis method is used to detect and estimate the parameters of maneuvering targets with constant acceleration. Otherwise, the precision of parameter estimation is difficult to meet the requirements. The number of pulses transmitted by airborne radar in a CPI is relatively small. When the pulse repetition rate is fixed, the less pulse number means the shorter coherent processing time. Therefore, it is difficult to apply the time-frequency analysis method directly to the research of maneuvering target detection and parameter estimation of airborne radar under the condition of short coherent processing time. In order to solve the above problems, the method of maneuvering target detection and parameter estimation proposed in this paper can obtain high precision of parameter estimation under the condition of short coherent processing time. The main contributions and innovations of this paper are as follows: firstly, the echo data model of airborne radar is introduced, and the echo data model of maneuvering target is deduced by describing the Doppler problem. A maneuvering target detection and parameter estimation method based on reconstructed signal and time sampling is proposed. The method can still obtain better estimation results of maneuvering target parameters under the condition of short coherent processing time. The parameter estimation performance is closer to the Cramer-Rao lower bound. Thirdly, a low complexity maneuvering target parameter estimation method based on compressed sensing and cubic phase transform (CPT) is proposed, which can sample and compress the signal at a frequency less than the sampling frequency required by Nyquist sampling theorem. In the case of short coherent processing time, this method can not only obtain accurate estimation results of maneuvering target parameters, but also lower computational complexity. Fourthly, the Cramer-Rao lower bound for the estimation of maneuvering target parameters is derived, which provides a theoretical basis for verifying the validity of the proposed algorithm in this paper.
【學位授予單位】：中國民航大學
【學位級別】：碩士
【學位授予年份】：2015
【分類號】：TN957.51

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