基于频谱感知的蒙特卡洛定位算法

Monte Carlo positioning algorithm based on spectrum sensing

为在未知信号源参数的情况下,仅根据接收到的观测信号对信号进行定位,结合频谱感知得到的接收信号强度(RSSI),提出一种分布式蒙特卡洛定位算法,从无线电信号传播损耗特性的物理层面出发,结合RSSI定位和蒙特卡洛方法,将传统的测距定位转换为概率学问题,利用不同检测节点的RSSI值的比较和四分法对信号源位置进行预测,缩小采样空间,增加更多的粒子滤波要求,达到提高定位精度的目的。仿真结果表明,相比于传统定位算法,该算法定位精度高,容错性好,能够减少由RSSI测量精度不高、检测节点频繁离开或加入引起的定位误差。

To locate the signal based on the received observation signal in the case of unknown signal source parameters,combined with the received signal strength(RSSI)obtained by spectrum sensing,a distributed Monte Carlo localization algorithm was proposed.From the perspectives of physical characteristics of propagation loss of radio signals,combined with RSSI positioning and Monte Carlo method,the traditional ranging location was converted into a probabilistic problem.The RSSI value of different detection nodes was compared and the quadrature method was used to predict the position of the signal source,reducing the sampling space and increasing particle filtering requirements were required to improve positioning accuracy.The simulation results show that compared with the traditional positioning algorithm,the proposed algorithm has high positioning accuracy and good fault tolerance,which can reduce the positioning error caused by the low accuracy of RSSI detection and frequent departure or addition of detection nodes.