Efficient cooperative localization algorithm in LOS/NLOS environments

The well-known cooperative localization algorithm, `sum-product algorithm over a wireless network´ (SPAWN) has two major shortcomings, a relatively high computational complexity and a large communication load. Using the Gaussian mixture model with a model selection criterion and the sigma-point (SP) methods, we propose the SPAWN-SP to overcome these problems. The SPAWN-SP easily accommodates different localization scenarios due to its high flexibility in message representation. Furthermore, harsh LOS/NLOS environments are considered for the evaluation of cooperative localization algorithms. Our simulation results indicate that the proposed SPAWN-SP demonstrates high localization accuracy in different localization scenarios, thanks to its high flexibility in message representation.