本文關(guān)鍵詞： 認(rèn)知雷達(dá) 自適應(yīng)能力 波形選擇 波形優(yōu)化 低截獲性能　出處：《電子科技大學(xué)》2016年碩士論文　論文類型：學(xué)位論文

【摘要】：寬帶認(rèn)知雷達(dá)是雷達(dá)智能化的結(jié)果。相比于傳統(tǒng)雷達(dá),它可以對(duì)目標(biāo)環(huán)境進(jìn)行自適應(yīng)的變換發(fā)射波形以適應(yīng)目標(biāo)環(huán)境的變化。認(rèn)知雷達(dá)的靈活性和自適應(yīng)性使得其受到雷達(dá)領(lǐng)域多方的關(guān)注,并成為近年來(lái)雷達(dá)領(lǐng)域研究的熱點(diǎn)。認(rèn)知是認(rèn)知雷達(dá)工作的基礎(chǔ),它通過(guò)對(duì)目標(biāo)特性和環(huán)境特性的認(rèn)知,確定環(huán)境狀態(tài)并記錄環(huán)境狀態(tài);自適應(yīng)算法是認(rèn)知雷達(dá)的核心,在得到環(huán)境狀態(tài)后,認(rèn)知雷達(dá)將根據(jù)環(huán)境狀態(tài)自適應(yīng)地選擇波形發(fā)射,以求達(dá)到最好的檢測(cè)效果。本文將針對(duì)以上兩個(gè)方面對(duì)寬帶認(rèn)知雷達(dá)進(jìn)行研究,并重點(diǎn)研究自適應(yīng)算法。本文主要工作內(nèi)容有:1.本文在基于認(rèn)知雷達(dá)原理的基礎(chǔ)上,首先對(duì)認(rèn)知雷達(dá)的雜波環(huán)境進(jìn)行了研究,并建立了能夠表達(dá)其特性的雜波模型;然后本文還對(duì)認(rèn)知雷達(dá)中的自適應(yīng)波形選擇的相關(guān)理論進(jìn)行了研究,包括動(dòng)態(tài)規(guī)劃理論及自適應(yīng)波形選擇模型。2.本文首先對(duì)經(jīng)典的目標(biāo)檢測(cè)算法和基于樣本信息累積分布的檢測(cè)算法的性能進(jìn)行了研究和仿真分析。然后,本文基于動(dòng)態(tài)規(guī)劃理論,展開(kāi)了對(duì)常規(guī)自適應(yīng)波形選擇算法的研究,主要研究了價(jià)值迭代算法、簡(jiǎn)化價(jià)值迭代算法和Q學(xué)習(xí)算法,并在這些研究基礎(chǔ)上研究了一種迭代步長(zhǎng)可變的Q學(xué)習(xí)算法。同樣,我們也通過(guò)仿真對(duì)比了不同算法的波形選擇準(zhǔn)確度,分析了自適應(yīng)算法性能的優(yōu)劣。3.本文針對(duì)雷達(dá)對(duì)波形低截獲性能的要求,研究了面向雷達(dá)低截獲性能的自適應(yīng)波形優(yōu)化算法。我們首先分析了影響雷達(dá)低截獲性能的因素和影響截獲因子的參數(shù),并且我們利用對(duì)不同基本信號(hào)的組合和編碼長(zhǎng)度的延長(zhǎng)等方法降低截獲因子,提高雷達(dá)的低截獲性能。經(jīng)過(guò)仿真,我們對(duì)比了優(yōu)化前后信號(hào)的模糊函數(shù)圖和截獲因子的變化情況,說(shuō)明了算法對(duì)波形優(yōu)化的有效性。4.本文針對(duì)認(rèn)知雷達(dá)對(duì)輔助知識(shí)信息的實(shí)時(shí)要求,研究了基于波形參數(shù)自適應(yīng)優(yōu)化的波形設(shè)計(jì)算法。算法根據(jù)前一組回波信號(hào),分析出雷達(dá)的環(huán)境情況和目標(biāo)情況,并通過(guò)優(yōu)化下一組波形的參數(shù)來(lái)達(dá)到對(duì)波形優(yōu)化的目的。經(jīng)過(guò)分析,我們發(fā)現(xiàn)了信號(hào)相位向量和信干噪比(SINR)的關(guān)系并選取相位參數(shù)作為優(yōu)化參數(shù)。經(jīng)過(guò)仿真,我們對(duì)比分析經(jīng)過(guò)相位參數(shù)優(yōu)化的信號(hào)表現(xiàn)出的檢測(cè)性能與優(yōu)化前信號(hào)檢測(cè)性能區(qū)別。
[Abstract]:Broadband radar is a radar intelligent cognitive results. Compared with the traditional radar, it can be adaptive to the target environment transform waveform in order to adapt to changes in the target environment. Radar cognitive flexibility and adaptability which received much attention and become a hot field of radar and radar field in recent years. Cognition is a cognitive basis for radar work, it based on the target characteristics and environment characteristics of cognition, determine the state of the environment and record the state of the environment; the adaptive algorithm is the core of cognitive radar, the state of the environment, cognitive radar will be adaptively selected according to environmental conditions in order to achieve the emission waveform, the best detection result. In this paper, in view of the above two aspects of research for broadband cognitive radar, and focuses on the adaptive algorithm. The main contents of this paper are: 1. based on the principle of cognitive radar Firstly, the clutter environment of cognitive radar is studied, and established the clutter model the expression characteristics; then the related theory of adaptive waveform selection in cognitive radar are studied, including dynamic programming theory and adaptive waveform selection model based on the classical.2. algorithm of target detection and performance testing the algorithm is based on the cumulative distribution of sample information is researched and simulated. Then, this paper based on the dynamic programming theory, researched on the conventional adaptive waveform selection algorithm, mainly studies the value iteration algorithm, simplifies the value iteration algorithm and Q learning algorithm, and based on the study of a variable step size the Q learning algorithm. Also, we are comparing different algorithms of waveform selection accuracy, analyzes the advantages and disadvantages of.3. the performance of the adaptive algorithm in this paper needle The requirements for the waveform performance of LPI radar, the study of adaptive waveform optimization algorithm for radar low interception performance. We first analyze the factors influencing the performance of LPI radar and parameters affecting the intercept factor, and we use different basic signal combinations and encoding length extension method to reduce the interception factor, improve the low probability of intercept the performance of the radar. After simulation, we compared the change of signal ambiguity function and the interception factor before and after optimization, the algorithm of waveform optimization effectiveness of.4. according to the real-time requirements of the auxiliary cognitive radar information and knowledge, on the waveform design algorithm based on adaptive waveform parameter optimization algorithm. According to the former group echo signal analysis, the environmental situation and the target of radar, and the parameter optimization of a set of waveforms to achieve the waveform optimization purposes. After analysis, we found that the signal phase vector and SINR (SINR) and the relationship between selected phase parameters as optimization parameters. By simulation, we compare the detection performance after showing phase parameter optimization and optimization of the signal before the signal detection performance difference.

【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2016
【分類號(hào)】：TN958

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