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新的全球定位系统弱信号高灵敏捕获算法
引用本文:陈景霞,李建文.新的全球定位系统弱信号高灵敏捕获算法[J].计算机应用,2012,32(11):3262-3267.
作者姓名:陈景霞  李建文
作者单位:陕西科技大学 电气与信息工程学院,西安710021
基金项目:西安市科技计划项目(CX1260-2)
摘    要:通过对弱信号条件下的全球定位系统(GPS)捕获算法的分析,建立了相干累加—非相干累加结合捕获算法的信号模型及检测概率模型。为了提高强弱信号并存时GPS卫星信号的捕获性能,提出一种采用序贯概率比检测方法的GPS捕获算法。对该方法和相干累加—非相干累加算法的检测概率、时间复杂度进行了分析比较,并进行了仿真验证。通过理论分析和计算机仿真,证明该方法在保证较高检测概率性能情况下,可以有效地缩短强弱信号并存时的检测时间,提高对GPS弱信号的捕获性能。

关 键 词:全球定位系统  序贯概率比检测  捕获  时间复杂度  
收稿时间:2012-05-11
修稿时间:2012-08-14

New GPS weak signal high-sensitivity acquisition algorithm
CHEN Jing-xia,LI Jian-wen.New GPS weak signal high-sensitivity acquisition algorithm[J].journal of Computer Applications,2012,32(11):3262-3267.
Authors:CHEN Jing-xia  LI Jian-wen
Affiliation:College of Electronical and Information Engineering, ShaanXi University of Science and Technology, Xian Shaanxi 710021, China
Abstract:The algorithm of weak Global Positioning System (GPS) signal capture was analyzed, and the coherent accumulation and non-coherent accumulation capture algorithms signal model and detecting probability model were built. In order to improve the performance of GPS signal acquisition when strong and weak signals both exist, this paper put forward a method of SPRT (Sequential Probability Ratio Test) to capture the GPS signal. This method with coherent accumulation and non-coherent accumulation capture algorithm in detecting probability and time complexity was compared and simulated. Through theoretical analysis and computer simulation, the SPRT method is proved of high detecting probability. It can effectively reduce the detection time when strong and weak signals both exist, and improve the performance of GPS weak signal acquisition.
Keywords:Global Positioning System (GPS)                                                                                                                          Sequential Probability Ratio Test (SPRT)                                                                                                                          acquisition                                                                                                                          time complexity
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