Time-Frequency Jointly Localization of the Moving Drones Based on the Bias Reduced Algorithm

To address the problem of improving drones localization accuracy in global positioning system (GPS) denial environments, this paper proposes a moving drones localization bias reduction algorithm based on the joint time-frequency domain. In this paper, a constrained weighted least squares (CWLS) problem is constructed based on the joint time difference of arrival (TDOA) and frequency difference of arrival (FDOA). To reduce bias from measurement noise and weighting matrix approximation, we incorporate a quadratic constraint into the CWLS problem, accounting for second-order noise and matrix errors. A bias reduced constrained weighted least squares (BR-CWLS) problem is formed and solved. Simulation results demonstrate the effectiveness of the BR-CWLS algorithm in reducing both the mean squared error and estimation bias when noise levels are low.