【摘要】：現(xiàn)代雷達(dá)若能夠根據(jù)周?chē)h(huán)境的變化自適應(yīng)地調(diào)整發(fā)射波形,并不斷地在與目標(biāo)環(huán)境的交互中獲得信息,對(duì)特定目標(biāo)進(jìn)行有效、可靠且穩(wěn)定地測(cè)量,將全面提高雷達(dá)的整體性能,更加適應(yīng)越來(lái)越復(fù)雜的戰(zhàn)場(chǎng)環(huán)境。因此,自適應(yīng)地選擇發(fā)射波形是當(dāng)前研究熱點(diǎn)之一。本文則研究了如何在跟蹤系統(tǒng)中實(shí)現(xiàn)波形自適應(yīng)選擇的問(wèn)題,給出了有/無(wú)雜波環(huán)境下跟蹤系統(tǒng)的波形自適應(yīng)選擇方法,為進(jìn)一步提升雷達(dá)探測(cè)與跟蹤性能提供了一定的理論依據(jù)。本文所做的研究工作如下:1、論文首先研究了無(wú)雜波環(huán)境下波形自適應(yīng)選擇問(wèn)題,基于Kalman濾波的波形自適應(yīng)選擇算法,根據(jù)目標(biāo)不同的運(yùn)動(dòng)狀態(tài),利用粒子群優(yōu)化算法自適應(yīng)設(shè)計(jì)跟蹤波形脈寬和調(diào)頻斜率,從實(shí)驗(yàn)方面分析了波形參數(shù)選擇對(duì)測(cè)量誤差、跟蹤精度的影響,仿真分析驗(yàn)證了文中所提算法的有效性。2、通過(guò)分析雷達(dá)信號(hào)脈寬與跟蹤性能的關(guān)系,對(duì)雷達(dá)信號(hào)參數(shù)進(jìn)行選擇,基于波形選擇準(zhǔn)則,實(shí)現(xiàn)了交互多模型(Interaction multiple model,IMM)的波形自適應(yīng)選擇算法,根據(jù)目標(biāo)運(yùn)動(dòng)狀態(tài)不同,自適應(yīng)設(shè)計(jì)下一時(shí)刻的發(fā)射信號(hào)脈寬,提高了目標(biāo)跟蹤性能,仿真驗(yàn)證了文中所提算法的有效性。3、分析了雜波環(huán)境下的波形自適應(yīng)選擇問(wèn)題,基于交互多模型數(shù)據(jù)關(guān)聯(lián)算法(Interacting multiple model probability data association,IMMPDA),設(shè)計(jì)了波形自適應(yīng)選擇方法,通過(guò)兩種不同的波形選擇準(zhǔn)則,提高了密集雜波條件下的目標(biāo)跟蹤性能,仿真驗(yàn)證了文中所提算法的有效性。
[Abstract]:If the modern radar can adjust the transmitting waveform adaptively according to the change of the surrounding environment, and continuously acquire the information in the interaction with the target environment, it can measure the specific target effectively, reliably and stably. It will improve the overall performance of radar and adapt to more and more complex battlefield environment. Therefore, adaptive selection of transmitting waveforms is one of the current research hotspots. In this paper, the problem of adaptive waveform selection in tracking system is studied, and the adaptive waveform selection method for tracking system with or without clutter is presented. It provides a theoretical basis for further improving radar detection and tracking performance. The research work in this paper is as follows: 1. In this paper, we first study the problem of waveform adaptive selection in clutter free environment. The adaptive waveform selection algorithm based on Kalman filter is based on different moving states of the target. Particle swarm optimization (PSO) algorithm is used to design tracking waveform pulse width and frequency modulation slope. The influence of waveform parameter selection on measurement error and tracking accuracy is analyzed experimentally. Simulation results verify the effectiveness of the proposed algorithm. By analyzing the relationship between radar signal pulse width and tracking performance, the radar signal parameters are selected based on waveform selection criteria. An adaptive waveform selection algorithm for interactive multi-model (Interaction multiple model-imm) is implemented. According to the different moving states of the target, the pulse width of the transmitted signal at the next moment is designed adaptively, and the target tracking performance is improved. Simulation results show that the proposed algorithm is effective. 3. The waveform adaptive selection problem in clutter environment is analyzed. An adaptive waveform selection method is designed based on the interactive multi-model data association algorithm (Interacting multiple model probability data association / IMMPDA). Through two different waveform selection criteria, the performance of target tracking under dense clutter is improved, and the effectiveness of the proposed algorithm is verified by simulation.
【學(xué)位授予單位】：江蘇科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TN953

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本文編號(hào)：2197468