关键词: 无线局域网室内定位, 似然函数模型, 蒙特卡罗, 克拉美罗界

Abstract:

The interference in the received power leads to the problem of the low estimation accuracy of WLAN indoor positioning, so a new method is proposed which constructs the maximum likelihood model and uses the Markov Chain Monte-Carlo sampling method to estimate position coordinates. The method considers taking the interference factor into the model, and uses the random sampling method to solve the estimation problem, which has the advantage of fast convergence and high estimate precision. Furthermore, the Cramer-Rao lower bound (CRLB) of the model is derived. In simulation experiment, the distribution of Cramer-Rao Bound in locating space is given. Finally, simulations show that the MCMC method can estimate the target location accurately. Under the same simulation conditions, the MCMC method achieves greater estimated precision and has a lower computational complexity than the Fletcher-Reeves Method (FR).

Key words: WLAN indoor positioning, likelihood model, Monte-Carlo, Cramer-Rao lower bound