Exploiting Spectral Resource Allocation Scheme for TDOA-Based Multiple Source Localization

In the field of spectrum monitoring, the common visibility of sensors to the radio frequency (RF) source is the basic condition for passive localization and has an important influence on the real-time localization rate (RTLR). This paper presents the structure of cognitive wireless localization network (CWLN), which aims to maximize the RTLR by adjusting the spectral resource allocation strategy of sensors. We first present the definition of the RTLR and then regard it as the objective to formulate an optimization problem, where the decision variables are the sensors' real-time central frequencies (RTCFs). Since the problem is highly nonlinear, genetic algorithm (GA) is introduced to solve the problem effectively, and the time complexity is acceptable for practical application. Simulation results show that the optimization of sensors' RTCFs is helpful to improve the RTLRs of CWLN with respect to the RF sources. Simulations also prove the superiority of the proposed algorithm over the other three baseline algorithms.