Adaptive cascaded high-resolution source localization based on collaboration of multi-UAVs

Effective information fusion is very important in hybrid source localization. In this paper, the performance analysis of conventional joint direction of arrival (DOA) and time difference of arrival (TDOA) system is derived and it is shown that this hybrid system may inferior to the single system when the ratio of angular measurements error to distance measurements error exceeds a threshold. To avoid this problem, an effective DOA/ TDOA adaptive cascaded (DTAC) technique is presented. The rotation feature of UAVs and spatial filtering technique are applied to gain the signal-to-noise ratio (SNR), which leads to more accurate estimation of time delay by using DOAs. Nevertheless, the time delay estimation precision is still limited by the sampling frequency, which is constrained by the finite load of UAV. To break through the limitation, an enhanced self-delay-compensation (SDC) method is proposed, which aims at detecting the overlooked time delay within the sampling interval by adding a tiny time delay. Finally, the position of the source is estimated by the Chan algorithm. Compared to DOA-only algorithm, TDOA-only algorithm and joint DOA/TDOA (JDT) algorithm, the proposed method shows better localization accuracy regardless of different SNRs and sampling frequencies. Numerical simulations are presented to validate the effectiveness and robustness of the proposed algorithm.