本文選題：機(jī)載單站被動定位 + PDRC定位法　； 參考：《中北大學(xué)》2017年碩士論文

【摘要】：隨著現(xiàn)有的單站被動定位技術(shù)的發(fā)展與濾波算法的完善,結(jié)合載機(jī)的機(jī)動性,本文針對傳統(tǒng)的彈載無線信標(biāo)機(jī)回收方法中存在的定位精度低、速度慢、范圍小的問題,重點(diǎn)從定位原理、誤差分析、參數(shù)測量以及濾波算法等角度進(jìn)行了一些研究工作:首先,針對機(jī)載單站被動定位,本文從角度變化率定位法(ARC)、相位差變化率定位法(PRC)、多普勒變化率定位法(DRC)三種方法的定位原理、單次目標(biāo)測量的誤差分析以及可觀測性方面進(jìn)行了仿真分析,給出了三種方法各自的優(yōu)缺點(diǎn)。其次,研究一種使用相位差、相位差變化率及多普勒變化率三個參數(shù)對目標(biāo)輻射源進(jìn)行定位的單站被動定位方法(PDRC法)。該方法減少了測量角度變化率這一參數(shù)的復(fù)雜,在減少工程難度的基礎(chǔ)上,PDRC具有更好的定位精度,定位誤差更小;為了提高定位參數(shù)的測量精度,還對獲取相位差變化率及多普勒變化率兩個參數(shù)的測量方法進(jìn)行了研究。最后,在分析擴(kuò)展卡爾曼濾波算法(EKF)、無味卡爾曼濾波算法(UKF)及施密特卡爾曼濾波算法(SOUKF)三種濾波算法基本原理的基礎(chǔ)上,研究了一種新的超球體無味卡爾曼濾波算法(Sqrt-UKFST),仿真結(jié)果表明該濾波算法的定位精度和收斂速度都優(yōu)于其他幾種算法。
[Abstract]:With the development of single station passive positioning technology and the improvement of filtering algorithm, combined with the maneuverability of the carrier, this paper aims at the problems of low positioning accuracy, slow speed and small range in the traditional recoverability method of the missile borne wireless beacon machine. This paper focuses on some research work from the aspects of positioning principle, error analysis, parameter measurement and filtering algorithm. In this paper, the positioning principle, error analysis and observability of angle change rate positioning method, phase difference change rate positioning method and Doppler change rate positioning method are analyzed. The advantages and disadvantages of the three methods are given. Secondly, a single station passive location method based on the three parameters of phase difference, phase difference change rate and Doppler change rate is studied. This method reduces the complexity of the parameter of measuring angle change rate, and on the basis of reducing the engineering difficulty, PDRC has better positioning accuracy and less positioning error, in order to improve the measuring accuracy of positioning parameters, The measurement methods of phase difference rate and Doppler rate are also studied. Finally, based on the analysis of the basic principles of the extended Kalman filtering algorithm (EKF), the tasteless Kalman filtering algorithm (UKF) and the Schmitt Kalman filtering algorithm (SOUKF), the basic principles of the three filtering algorithms are analyzed. A new hypersphere tasteless Kalman filter algorithm named Sqrt-UKFSTT is studied in this paper. The simulation results show that the location accuracy and convergence speed of the proposed algorithm are better than those of other algorithms.
【學(xué)位授予單位】：中北大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TJ06;TN713

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