【摘要】 针对目前定位算法存在精度与成本有较大矛盾的问题,在定位实施各阶段采取有效措施,提出一种新的基于接收信号强度指示(RSSI)观测模型的协作定位算法。该算法以有效计算方式获得距离数据,优选锚节点参与定位计算,通过泰勒展开迭代求精法实施位置优化,最终获得满足要求且定位精度较高的位置估计。引入协作定位思想,将满足一定要求的已定位节点升级为锚节点,参与其他节点的定位,提高了定位的覆盖率和定位精度。仿真实验结果显示:网络参数相同的条件下,本文算法定位效果接近基于实际坐标的泰勒级数展开算法,而远高于基本的最小二乘定位算法,且由于所需存储空间小,其定位精度也随测距误差的减小而快速提高,能够满足大规模无线传感器网络的定位需求。更多还原

【Abstract】 Aiming at the problem that there is a great contradiction between the precision and cost of the current location algorithm,a new cooperative localization algorithm based on received signal strength indicator(RSSI)observation model is proposed. Using effective calculation method,the positioning calculation is carried out by obtaining the distance data and the optimally selecting anchor and applying the Taylor expansion iterative refinement method to optimize the position,finally obtains the location estimates with high positioning accuracy. In the positioning process,the concept of cooperative positioning is introduced,in which the positioned node meeting the certain requirements will be upgraded to anchor node,so that it can participate in the positioning of other nodes,and improve the coverage and positioning accuracy. Simulation experiment results show that on the premise of the same network pa-rameters,the positioning effect of the proposed algorithm is close to the Taylor series expansion algorithm based on the actual coordinates,and much higher than the basic least square algorithm. And because the storage space is small,the positioning accuracy is improved rapidly with the decrease of ranging error,which can meet the needs of large-scale wireless sensor networks.更多还原