基于动态T检验的修正最小二乘BFGS定位算法

MODIFIED LEAST SQUARES-BFGS POSITIONING ALGORITHM BASED ON DYNAMIC T-TEST

针对传统基于接收信号强度指示RSSI(Received Sgnal Strength Indicator)的最小二乘定位算法精度有限的问题，从降低信号噪声影响出发，提出一种基于动态T检验的修正最小二乘-BFGS定位算法。在测距阶段，将T检验法动态应用于RSSI值筛选，以消除较大测量误差影响，提高测距精度;定位阶段，先基于平均测算距离对传统的最小二乘法进行修正，提升初步定位精度0.3~2米;在此基础上，以信号强度误差最小为目标优化函数，基于BFGS算法对修正最小二乘法计算的初值进行迭代求精，以进一步提高定位精度。仿真实验表明，该算法有效提升了定位精度，在100mxlOOm范围内可比传统最小二乘定位误差降低4~11米。

Conventional least-squares ( L S ) positioning algorithm based on received signal strength indicator ( RSS I ) has limitation in positioning precision. In view of this, from the perspective of reducing the impact of signal noise, we presented a dynamic T -test-based modified least squares-BFGS positioning algorithm. In stage of RSSI ranging, in order to eliminate the influence of larger measurement errors and to improve measuring precision, we applied the T-test to RSSI values screening dynamically. In stage of positioning, we first modified the conventional LS algorithm based on average estimation distance to enhance the initial positioning accuracy by 0. 3 ~ 2 meters. O n this basis,we took the minimisation of signal strength error as the function of target optimisation, and made iterative improvement on the initial value calculated by modified LS algorithm based on B F G S algorithm to further improve positioning accuracy. Simulation experimental results showed that the algorithm effectively improved the positioning accuracy, compared with conventional LS positioning algorithm, its error decreased by 4 ?llmeter in a range of 100 m x 100 m .