發(fā)布時間：2018-06-25 03:48

  本文選題：導航接收機 + 載波恢復　； 參考：《國防科學技術大學》2014年碩士論文

【摘要】：隨著衛(wèi)星導航技術的不斷發(fā)展和應用,人們對導航服務性能的需求不斷提升,特別是弱信號條件下的服務性能。由于信號強度較低,在弱信號下載波跟蹤環(huán)路容易失鎖,不能實現(xiàn)穩(wěn)定的跟蹤。針對該問題,本文研究了弱信號下的卡爾曼濾波載波恢復算法。論文的研究工作主要從以下四個方面展開:(1)總結歸納了傳統(tǒng)的載波恢復方法,詳細介紹了載波恢復環(huán)路中影響性能的鑒相器、鑒頻器和環(huán)路濾波器。針對傳統(tǒng)的載波恢復模型在弱信號容易出現(xiàn)失鎖的問題,本文在傳統(tǒng)的鎖相環(huán)載波恢復模型的基礎上,利用卡爾曼濾波器替代了其中的環(huán)路濾波器,建立了卡爾曼濾波載波恢復模型。(2)相位卡爾曼濾波的原始輸入為鑒相器的輸入,鑒別結果的好壞及卡爾曼濾波積分時間直接決定了卡爾曼濾波的性能。目前的研究主要針對給定積分時間的跟蹤性能問題,沒有針對卡爾曼濾波積分時間優(yōu)化選擇的研究。本文建立了鑒相器的噪聲模型,結合鑒相器噪聲模型和卡爾曼濾波載波恢復模型,以穩(wěn)態(tài)卡爾曼濾波相位標準差最小為準則針對積分時間進行優(yōu)化設計。針對相位卡爾曼濾波載波恢復算法在低載噪比下容易發(fā)生載波周跳的問題,本文提出了一種控制新息幅度的周跳抑制方法。(3)在高動態(tài)應用中,傳統(tǒng)的鑒相器無法滿足高動態(tài)跟蹤需求,需要使用鑒頻器對頻率進行鑒別,并作為卡爾曼濾波器的原始觀測量。頻率卡爾曼濾波也需要針對積分時間進行優(yōu)化設計。本文研究了鑒頻器的噪聲模型,結合鑒頻器噪聲模型和卡爾曼濾波頻率估計模型,以穩(wěn)態(tài)卡爾曼濾波頻率標準差最小為準則針對積分時間進行優(yōu)化設計。(4)結合本文中提出的積分時間優(yōu)化,利用穩(wěn)態(tài)卡爾曼濾波器作為環(huán)路濾波器,本文給出了一種應用協(xié)處理器的跟蹤環(huán)路設計方案。設計硬件加速器和相關值預處理的方式增強了協(xié)處理器的性能。該方案簡化了基帶處理芯片設計,可直接應用于導航接收機基帶芯片開發(fā)。
[Abstract]:With the development and application of satellite navigation technology, the demand for navigation service performance is increasing, especially under the condition of weak signal. Because of the low signal intensity, it is easy to lose the lock in the weak signal download wave tracking loop and can not achieve stable tracking. To solve this problem, the Kalman filter carrier recovery algorithm for weak signals is studied in this paper. The main work of this paper is as follows: (1) the traditional carrier recovery methods are summarized, and the phase discriminator, frequency discriminator and loop filter which affect the performance of the carrier recovery loop are introduced in detail. Aiming at the problem that the traditional carrier recovery model is prone to lose lock in weak signal, the Kalman filter is used to replace the loop filter on the basis of the traditional phase-locked loop carrier recovery model. The carrier recovery model of Kalman filter is established. (2) the original input of phase Kalman filter is the input of phase discriminator. The performance of Kalman filter is directly determined by the quality of discriminating result and the integral time of Kalman filter. The current research focuses on the tracking performance of given integral time, and there is no research on the optimal selection of Kalman filter integral time. In this paper, the noise model of the phase discriminator is established. Combining the noise model of the phase discriminator and the Kalman filter carrier recovery model, the integration time is optimized based on the minimum standard deviation of the steady-state Kalman filter phase. Aiming at the problem that phase Kalman filter carrier recovery algorithm is easy to occur carrier cycle slip at low carrier / noise ratio, a cycle slip suppression method to control the amplitude of innovation is proposed in this paper. (3) in high dynamic applications, The traditional phase discriminator can not meet the high dynamic tracking requirement, so it is necessary to use frequency discriminator to identify the frequency and to be the original observation of Kalman filter. The frequency Kalman filter also needs to be optimized for integral time. In this paper, the noise model of the discriminator is studied, which combines the noise model of the discriminator and the Kalman filter frequency estimation model. The minimum standard deviation of steady-state Kalman filter frequency is taken as the criterion to optimize the integration time. (4) combined with the integration time optimization proposed in this paper, the steady-state Kalman filter is used as the loop filter. This paper presents a design scheme of tracking loop with coprocessor. The design of hardware accelerator and correlation value preprocessing enhances the performance of the coprocessor. This scheme simplifies the design of baseband processing chip and can be directly applied to the development of baseband chip of navigation receiver.
【學位授予單位】：國防科學技術大學
【學位級別】：碩士
【學位授予年份】：2014
【分類號】：TN965.5

【參考文獻】

相關期刊論文 前10條

1 顧睿文;黃仰博;蘇映雪;歐鋼;;基于FPGA的導航接收機跟蹤環(huán)路設計與實現(xiàn)[J];全球定位系統(tǒng);2014年05期

2 林文興;;高動態(tài)GNSS導航接收機中擴展卡爾曼跟蹤算法的研究[J];電子世界;2014年02期

3 趙文駿;茅旭初;;基于自適應濾波的微弱GPS信號跟蹤方法[J];計算機仿真;2013年08期

4 周廣宇;茅旭初;林慶恩;曹意;;基于雙卡爾曼濾波及貝葉斯估計的微弱GPS信號跟蹤方法[J];上海交通大學學報;2010年09期

5 唐小妹;黃仰博;王飛雪;;導航接收機中基于反正切鑒別器載波環(huán)路的分析及優(yōu)化設計[J];電子與信息學報;2010年07期

6 唐小妹;徐鵬程;王飛雪;;兩種相位鑒別器下的導航接收機跟蹤環(huán)路性能分析及比較[J];國防科技大學學報;2010年02期

7 邢兆棟;趙維剛;;基于NIOSII的多模導航接收機跟蹤環(huán)路[J];無線電工程;2009年08期

8 周廣宇;茅旭初;;基于平方根卡爾曼濾波的微弱GPS信號跟蹤方法[J];上海交通大學學報;2009年07期

9 李金海;巴曉輝;陳杰;;三階卡爾曼濾波數(shù)字鎖頻環(huán)設計及性能分析[J];電子科技大學學報;2008年05期

10 曾富華;汪遠玲;楊萬麟;;一種基于擴展卡爾曼濾波器的頻率及頻率斜率估計算法[J];電訊技術;2008年03期

相關會議論文 前1條

1 王建輝;牟衛(wèi)華;歐鋼;;一種延長弱信號環(huán)境下載波環(huán)平均周跳時間的方法[A];第一屆中國衛(wèi)星導航學術年會論文集（上）[C];2010年

相關碩士學位論文 前1條

1 吳舜曉;全數(shù)字導航接收機協(xié)處理器技術研究[D];國防科學技術大學;2009年

，

本文編號：2064423