Abstract
Passive localization of the wireless signal source attracts a considerable level of research interest for its wide applications in modern wireless communication systems. To accurately locate the signal source passively in the downtown area, sensors are carried on the unmanned aerial vehicles flying in the air, where the wireless sensor network can be established with an optimal geometry configuration conveniently. In this case, the influence of multipath fading can be avoided and the time difference of arrival measurement can be estimated precisely in Rician channel. By employing the operating center as a calibration source to refine the positions of the unmanned aerial vehicles, we present a simplified formulation of the time difference of arrival localization method according to the min-max criterion. To accurately estimate the position of the source, the nonlinear equations are relaxed using semidefinite programming to obtain an initial solution, which is utilized as the starting point of the iterative algorithm to refine the solution. In the simulation section, the validity and the robustness of the proposed methods are verified through the performance comparison with the Cramer–Rao lower bound.
Highlights
The sensors loaded on the unmanned aerial vehicle (UAV) form a micro wireless sensor network (WSN) in the air, and taking full advantage of the controllable UAV, we present a more precise estimation method to locate the signal source in the downtown area
We present the optimal geometry distribution of the UAV during passive localization of the signal source, and its more accurate performance is verified in the simulation
The two-step weighted least squares (TWLS) localization method is adopted for the performance comparison to locate the calibration source to refine the positions of the UAVs, and the accurate position of the signal source is obtained according to the classical iterative algorithm, where the starting point is generated by the semidefinite programming (SDP) technology
Summary
With the rapid development of information technologies and wireless communications, passive localization of the signal source has been of considerable interest in several fields such as wireless communications,[1,2,3] sensor networks,[4,5,6] microphone arrays,[7,8] sonar,[9,10] and electronic warfare (EW).[11,12,13] The passive localization technology only locates the position of the source through receiving the electromagnetic signals, which does not need the surveillance equipment transmitting a radio signal to the measured target. When the uncooperative signal source radiates the wireless signal into the space, the synchronized sensors loaded on the UAVs capture it immediately, and all the received signals are sent to the operating center, where the localization algorithm is executed and the position of the signal source can be obtained. Due to the special geometry configuration of the UAV group, it is probable to have an interesting phenomenon that all of the obtained TDOA values are D^tj = 0, j = 2, 3, 4 when p1 is chosen as the reference node In this case, we can confirm that the position of the signal source q is at the subpoint of the reference sensor p1 on the ground. To further refine the localization accuracy, the estimation will be taken as the initial starting point of the iterative algorithm
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