Grey Wolf Optimisation and TDOA Co-Location in Traditional Chinese Medicine Warehousing

In the nonline-of-sight (NLOS) environment of herbal medicine storage, the traditional CHAN and FANG algorithms have significantly degraded the localisation accuracy and even the data are not available. In this paper, we propose a collaborative localisation algorithm that combines grey wolf optimisation and TDOA. Firstly, the TDOA geometric positioning algorithm processes the arrival time difference to obtain the optimal solution; then, the grey wolf optimization algorithm further processes the optimal solution, and after iteration, it obtains the estimation of the minimum fitness, i.e., the exact location of the Chinese herbal medicine box. Simulation results show that the algorithm can effectively resist NLOS interference and provide accurate positioning. Compared with the original TDOA geometric positioning algorithm, the algorithm in this paper improves the average positioning accuracy by 25.9% and 12.1% under different initial points and noise levels, respectively.