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联合RSSD和TDOA技术的认知协同定位算法研究
引用本文:林绪森,王红军,王伦文.联合RSSD和TDOA技术的认知协同定位算法研究[J].信号处理,2016,32(8):931-936.
作者姓名:林绪森  王红军  王伦文
基金项目:国家自然科学基金(61273302)
摘    要:在认知无线网络通信中,主用户的位置信息对于认知用户借用信道接入通信具有重要意义,通过协同定位技术来提高定位性能已成为当前认知无线电领域研究热点之一。论文提出了一种基于RSSD/TDOA技术的协同定位算法,该算法适用于对主用户发射功率和主用户信号发射瞬时时间等先验知识未知的应用场景。算法首先通过凸包算法对主用户的位置进行识别,然后再采用RSSD/TDOA协同算法对主用户进行定位,并通过顽健性较强的泰勒级数展开法来提高定位精度。仿真结果表明,论文所提的在认知无线网络中实现对主用户定位的算法相比较而言具有更高的定位精度和时效性。 

关 键 词:认知无线网络    凸包算法    RSSD/TDOA算法    泰勒级数展开法
收稿时间:2016-02-01

Cognitive Cooperative Location Algorithm Research Based on RSSD and TDOA Technology
Abstract:Position information of primary user is critical for communication between CR users in cognitive radio network. By cooperative location technology to improve the positioning performance has become a hot research direction in cognitive radio network recently. Based on RSSD/TDOA, a cooperative location algorithm is proposed in detail in this paper. The algorithm is suitable for the application scenarios that the priori knowledge is unknown such as transmit power and signal transmission instantaneous time of the primary user. Firstly the algorithm divide the consideration area into two cases: inner area and outer area by convex hull algorithm. Then the cooperative location algorithm based on RSSD/TDOA is adopted to estimate position of the primary user. Taylor series expansion algorithm is applied in order to enhance the location accuracy. In simulation results, we compare the performance and time of the RSSD, TDOA estimation and algorithm proposed in this paper. The result of simulation shows that the proposed algorithm has better performance of location and time duration comparing with other algorithms in cognitive radio field. 
Keywords:
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