本文選題：雷達資源管理 + 目標跟蹤算法　； 參考：《電子科技大學(xué)》2014年碩士論文

【摘要】：雷達是現(xiàn)代軍事信息化戰(zhàn)場中必不可少的高科技裝備,隨著隱身技術(shù)的發(fā)展和電磁環(huán)境的日益惡劣,雷達正在向自適應(yīng)、多功能的方向發(fā)展。雷達資源管理就是提高雷達性能的手段之一,其實質(zhì)是對雷達任務(wù)參數(shù)進行有效的配置,達到節(jié)約系統(tǒng)資源、充分發(fā)揮系統(tǒng)性能的目的。雷達資源管理可分為搜索任務(wù)管理、跟蹤任務(wù)管理和波束駐留調(diào)度三個方面。在跟蹤模塊下進行資源管理主要是指通過對采樣周期的控制來管理時間資源,對發(fā)射波形相關(guān)參數(shù)的控制來管理能量資源,最終在保證跟蹤精度的前提下使系統(tǒng)參數(shù)得到最優(yōu)化配置。本文圍繞雷達資源管理下的跟蹤模塊進行研究,首先,從目標跟蹤算法出發(fā),介紹了卡爾曼濾波、???濾波和?????濾波三種基本目標跟蹤算法以及“當前”統(tǒng)計模型(Current Statistical Model,CSM)濾波、自適應(yīng)???濾波、交互多模型(Interacting Multiple Model,IMM)濾波三種機動目標跟蹤算法。從跟蹤性能和時間消耗兩方面對三種機動目標跟蹤算法進行了評估,通過仿真驗證了IMM濾波具有更高的跟蹤精度,CSM濾波的實時性更好。其次,針對相控陣雷達研究了三種基于自適應(yīng)目標跟蹤的資源管理算法。三種算法都是在CSM算法的基礎(chǔ)上實現(xiàn)的。前兩種算法分別利用預(yù)測協(xié)方差門限控制球坐標系下的預(yù)測協(xié)方差實現(xiàn)采樣周期的自適應(yīng)變化,利用期望跟蹤精度控制球坐標系下的預(yù)測的估計誤差協(xié)方差實現(xiàn)脈沖重復(fù)個數(shù)的自適應(yīng)變化,他們分別對時間資源和能量資源進行了管理。第三種算法是前兩種算法的結(jié)合,同時實現(xiàn)了采樣周期和脈沖重復(fù)個數(shù)的自適應(yīng)變化。仿真驗證了三種方法的有效性以及全自適應(yīng)參數(shù)情況下的優(yōu)勢。最后,結(jié)合雷達的射頻隱身技術(shù),對具有MIMO(Multiple Input Multiple Output)模式的新體制雷達進行了跟蹤時的資源管理。在建立該問題的優(yōu)化模型時,根據(jù)傳統(tǒng)雷達截獲因子的概念,推導(dǎo)了MIMO雷達截獲因子的表達式,將其作為使雷達射頻隱身性能優(yōu)化的目標函數(shù),模型的約束條件則是與預(yù)測協(xié)方差和回波信噪比相關(guān)的。模型中的優(yōu)化參數(shù)為子陣劃分個數(shù)、平均發(fā)射功率、波束駐留時間和采樣周期,通過遺傳算法對該模型的求解驗證了該目標跟蹤算法能提升MIMO雷達的射頻隱身性能和跟蹤精度。
[Abstract]:Radar is an indispensable high-tech equipment in the modern military information battlefield. With the development of stealth technology and the increasingly bad electromagnetic environment, radar is developing in the direction of self-adaptation and multi-function. Radar resource management is one of the methods to improve radar performance. Its essence is to effectively configure radar mission parameters to save system resources and give full play to system performance. Radar resource management can be divided into three aspects: search task management, tracking task management and beam resident scheduling. Resource management under the tracking module mainly refers to the control of the sampling period to manage the time resources and the control of the parameters related to the transmitting waveform to manage the energy resources. Finally, the system parameters are optimized under the premise of ensuring tracking accuracy. In this paper, the tracking module under radar resource management is studied. Firstly, the Kalman filter is introduced from the target tracking algorithm. Filtering and filtering? Filter three basic target tracking algorithms and "current Statistical Model CSM" filtering, adaptive? There are three maneuvering target tracking algorithms: filtering, interactive Multiple model filtering. Three maneuvering target tracking algorithms are evaluated in terms of tracking performance and time consumption. Simulation results show that IMM filter has higher tracking accuracy and better real-time performance. Secondly, three resource management algorithms based on adaptive target tracking are studied for phased array radar. All three algorithms are implemented on the basis of CSM algorithm. The first two algorithms use predictive covariance threshold to control the predictive covariance in spherical coordinate system to realize the adaptive change of sampling period. The covariance of prediction error in spherical coordinate system is controlled by the expected tracking precision to realize the adaptive variation of the number of pulse repeats. They manage the time resources and the energy resources respectively. The third algorithm combines the first two algorithms and adaptively changes the sampling period and the number of pulse repeats at the same time. Simulation results show the effectiveness of the three methods and the advantages of fully adaptive parameters. Finally, combined with the radio frequency stealth technology of radar, the resource management of the new system radar with MIMO(Multiple Input Multiple output mode is carried out. Based on the concept of the traditional radar interception factor, the expression of the MIMO radar interception factor is derived, which is regarded as the objective function to optimize the radar radio frequency stealthy performance. The constraints of the model are related to the prediction covariance and echo signal-to-noise ratio (SNR). The optimized parameters in the model are subarray number, average transmit power, beam-dwell time and sampling period. It is proved by genetic algorithm that the target tracking algorithm can improve the radio-frequency stealth performance and tracking accuracy of MIMO radar.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2014
【分類號】：TN953

【參考文獻】

相關(guān)期刊論文 前1條

1 李軍政;;飛行器射頻隱身技術(shù)發(fā)展[J];現(xiàn)代導(dǎo)航;2012年03期

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本文編號：1815494