本文選題：認(rèn)知雷達(dá) + 自適應(yīng)�。� 參考：《國(guó)防科學(xué)技術(shù)大學(xué)》2014年博士論文

【摘要】：現(xiàn)有雷達(dá)系統(tǒng)的發(fā)射波形和工作模式一般固定不變,接收系統(tǒng)僅被動(dòng)地處理雷達(dá)信號(hào)和數(shù)據(jù),使得即使精心設(shè)計(jì)的雷達(dá)系統(tǒng)也難以在復(fù)雜的時(shí)空多變環(huán)境中獲得理想的處理性能。認(rèn)知雷達(dá)具有接收機(jī)到發(fā)射機(jī)的閉環(huán)反饋機(jī)制,能夠根據(jù)先驗(yàn)和實(shí)時(shí)的環(huán)境及目標(biāo)知識(shí)自適應(yīng)動(dòng)態(tài)調(diào)整雷達(dá)收發(fā)系統(tǒng),從根本上改變了傳統(tǒng)雷達(dá)單向的信息處理方式,能夠大幅提高雷達(dá)系統(tǒng)性能和環(huán)境適應(yīng)能力,具有重要的理論研究和軍事應(yīng)用價(jià)值,受到國(guó)內(nèi)外很多專(zhuān)家學(xué)者和軍方的廣泛關(guān)注。自適應(yīng)發(fā)射波形優(yōu)化技術(shù)是認(rèn)知雷達(dá)系統(tǒng)的基礎(chǔ)關(guān)鍵技術(shù)之一,論文主要研究了面向目標(biāo)參數(shù)估計(jì)問(wèn)題的雷達(dá)發(fā)射系統(tǒng)自適應(yīng)優(yōu)化調(diào)整技術(shù),具體內(nèi)容可分為目標(biāo)跟蹤(運(yùn)動(dòng)目標(biāo)狀態(tài)估計(jì))和雷達(dá)成像(靜止目標(biāo)電磁散射系數(shù)估計(jì))兩個(gè)方面:在目標(biāo)跟蹤方面,研究了雜波環(huán)境下以提高機(jī)動(dòng)目標(biāo)跟蹤精度為目的的自適應(yīng)波形選擇技術(shù)。論文首先對(duì)雷達(dá)接收系統(tǒng)和跟蹤測(cè)量數(shù)據(jù)獲取過(guò)程進(jìn)行了詳細(xì)建模,分析了不同信噪比情況下雷達(dá)發(fā)射波形對(duì)測(cè)量數(shù)據(jù)統(tǒng)計(jì)特性的影響及定量計(jì)算方法,并設(shè)計(jì)了與自然界中蝙蝠發(fā)射聲波信號(hào)類(lèi)似的CF-HFM(Constant Frequency-Hyperbolic Frequency Modulation)雷達(dá)脈沖串波形,提出了雜波環(huán)境下基于雷達(dá)任務(wù)的機(jī)動(dòng)目標(biāo)跟蹤自適應(yīng)波形選擇算法及自適應(yīng)發(fā)射波形與檢測(cè)門(mén)限聯(lián)合優(yōu)化方法;其次,為了較為精確地估計(jì)機(jī)動(dòng)目標(biāo)混合運(yùn)動(dòng)狀態(tài)后驗(yàn)概率密度函數(shù),提出了一種完全分離連續(xù)基狀態(tài)與離散模型狀態(tài)估計(jì)的交互多模型概率數(shù)據(jù)關(guān)聯(lián)粒子濾波器(Interacting Multiple Model Probabilistic Data Association Particle Filter,IMMPDAPF),估計(jì)循環(huán)僅需要基狀態(tài)粒子,能夠控制每個(gè)運(yùn)動(dòng)模型對(duì)應(yīng)的粒子數(shù),并引入穩(wěn)健性較好的Amariα-散度表征不同發(fā)射波形對(duì)應(yīng)雷達(dá)測(cè)量數(shù)據(jù)包含的信息量,提出了與IMMPDAPF實(shí)現(xiàn)過(guò)程緊密結(jié)合的雜波環(huán)境下基于信息論準(zhǔn)則的機(jī)動(dòng)目標(biāo)跟蹤自適應(yīng)波形選擇算法。在雷達(dá)成像方面,研究了以降低成像處理復(fù)雜度為目的的自適應(yīng)發(fā)射分集技術(shù)和基于發(fā)射分集的曲線(xiàn)彈道合成孔徑雷達(dá)(Synthetic Aperture Radar,SAR)成像算法。首先,針對(duì)以景象匹配制導(dǎo)為目的的曲線(xiàn)彈道SAR成像問(wèn)題,提出通過(guò)自適應(yīng)調(diào)整雷達(dá)波束指向使雷達(dá)近似工作于等效正側(cè)視幾何下,能夠大大減小距離徙動(dòng)校正難度及回波信號(hào)方位向和距離向耦合,并在此基礎(chǔ)上設(shè)計(jì)了利用部分孔徑數(shù)據(jù)和高效頻譜分析方法的RD-Dechirp(Range Doppler-Dechirp)快視成像算法;其次,針對(duì)以尋的制導(dǎo)為目的大斜視曲線(xiàn)彈道SAR成像問(wèn)題,通過(guò)在雷達(dá)發(fā)射信號(hào)中引入自適應(yīng)調(diào)整的非線(xiàn)性調(diào)頻分量,提出了曲線(xiàn)彈道SAR非線(xiàn)性調(diào)頻變標(biāo)(Nonlinear Chirp Scaling,NCS)成像算法,能夠同時(shí)處理大斜視曲線(xiàn)彈道情況下距離徙動(dòng)校正和二次距離壓縮的方位頻率依賴(lài)性和距離空變性,算法計(jì)算量與標(biāo)準(zhǔn)CS算法及RD算法相當(dāng),提供了成像性能與計(jì)算量的完美折中;最后,針對(duì)任意航跡和斜視幾何情況下的聚束SAR成像問(wèn)題,提出了基于PRI(Pulse Repetition Interval)自適應(yīng)調(diào)整的PFA(Polar Format Algorithm)成像算法,能夠避免原始PFA算法的插值操作和利用全部波數(shù)域數(shù)據(jù)進(jìn)行成像,生成高質(zhì)量SAR圖像僅需要FFT和復(fù)乘運(yùn)算,能夠兼顧平臺(tái)航跡靈活性、成像精度及成像效率。論文充分利用雷達(dá)接收系統(tǒng)到發(fā)射系統(tǒng)的反饋機(jī)制和先驗(yàn)知識(shí),研究了面向目標(biāo)參數(shù)估計(jì)問(wèn)題的雷達(dá)發(fā)射系統(tǒng)自適應(yīng)調(diào)整技術(shù)和方法,研究成果有助于從根本上改變現(xiàn)有雷達(dá)系統(tǒng)的工作方式,提高現(xiàn)有雷達(dá)系統(tǒng)的工作性能和復(fù)雜環(huán)境適應(yīng)能力,為推動(dòng)我國(guó)雷達(dá)系統(tǒng)的智能化和認(rèn)知雷達(dá)技術(shù)的實(shí)用化提供基礎(chǔ)理論和關(guān)鍵技術(shù)支撐。
[Abstract]:The transmission waveform and working mode of the existing radar system are generally fixed, and the receiving system only passively handles radar signals and data, so that even carefully designed radar systems can not obtain ideal processing performance in complex spatio-temporal environment. The cognitive radar has closed loop feedback mechanism to the transmitter to the transmitter. According to the prior and real-time environment and target knowledge, the adaptive dynamic adjustment of radar transceiver system has fundamentally changed the one-way information processing mode of the traditional radar, and can greatly improve the performance of the radar system and the adaptability of the environment. It has important theoretical research and military application value. It has been widely used by many experts and scholars at home and abroad and the military. The adaptive transmission waveform optimization technique is one of the key technologies of the cognitive radar system. The paper mainly studies the adaptive optimization and adjustment technology of radar launching system for target parameter estimation. The specific content can be divided into target tracking (moving target state estimator) and radar imaging (the static target electromagnetic scattering coefficient). The two aspects: in target tracking, the adaptive waveform selection technique for improving the tracking precision of maneuvering target is studied in the environment of clutter. Firstly, the process of radar receiving system and tracking measurement data acquisition is modeled in detail, and the data statistics of radar emission waveform for different signal to noise ratio are analyzed. The influence of the characteristic and the quantitative calculation method, and design the CF-HFM (Constant Frequency-Hyperbolic Frequency Modulation) radar pulse string similar to the bats' acoustic signal in the natural world, and put forward the adaptive waveform selection algorithm for the maneuvering target tracking based on the radar task and the adaptive emission waveform and detection. In order to accurately estimate the posterior probability density function of the mixed motion state of the maneuvering target, an interactive multi model probabilistic data association particle filter (Interacting Multiple Model Probabilistic Data Association Par) is proposed for the precise estimation of the post probability density function of the mixed motion state of the maneuvering target. Ticle Filter, IMMPDAPF), it is estimated that the cycle only needs the basic state particles, can control the number of particles corresponding to each motion model, and introduces the good robust Amari alpha divergence to characterize the information contained in the radar measurement data of different emission waveforms, and puts forward the information theory based on the information theory based on the clutter environment which is closely combined with the IMMPDAPF implementation process. The adaptive waveform selection algorithm for maneuvering target tracking is proposed. In the aspect of radar imaging, the adaptive transmit diversity technique which aims to reduce the complexity of imaging processing and the Synthetic Aperture Radar (SAR) imaging algorithm based on the emission diversity are studied. In line ballistic SAR imaging, it is proposed that using adaptive adjustment of radar beam direction to make radar approximate to the equivalent positive side view geometry, it can greatly reduce the difficulty of distance migration correction and the azimuth and range coupling of echo signals. On this basis, a RD-Dechirp (Ran) using partial aperture data and high efficiency spectrum analysis method is designed. Ge Doppler-Dechirp) fast vision imaging algorithm; secondly, aiming at the problem of SAR imaging of large squint trajectory with the aim of homing guidance, a nonlinear frequency modulation (Nonlinear Chirp Scaling, NCS) imaging algorithm of curve ballistic SAR (Nonlinear Chirp Scaling, NCS) is proposed by introducing the adaptive adjusting nonlinear frequency modulation component in the radar transmitting signal. Considering the azimuth frequency dependence and distance space variability of distance migration correction and two distance compression in the case of curve trajectory, the computational complexity of the algorithm is equivalent to the standard CS algorithm and the RD algorithm, which provides a perfect compromise between the imaging performance and the computational complexity. Finally, the PRI (P) is proposed for the cluster SAR imaging problem under arbitrary track and squint geometry. Ulse Repetition Interval) adaptive PFA (Polar Format Algorithm) imaging algorithm can avoid the interpolation operation of the original PFA algorithm and use all the data of the wavenumber domain to imaging. The generation of high quality SAR images requires only FFT and multiplicative operation. It can give consideration to the flexibility of the platform track, the imaging precision and the imaging efficiency. The paper is fully profitable. By using the feedback mechanism and prior knowledge of radar receiving system to the launch system, the adaptive adjustment technology and method of radar launching system for target parameter estimation are studied. The research results help to fundamentally change the working mode of the existing radar system and improve the performance of the existing radar system and the adaptability of the complex environment. It provides basic theoretical and key technical support for promoting the intellectualization of radar system and the practicality of cognitive radar technology in China.

【學(xué)位授予單位】：國(guó)防科學(xué)技術(shù)大學(xué)
【學(xué)位級(jí)別】：博士
【學(xué)位授予年份】：2014
【分類(lèi)號(hào)】：TN958

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