An efficient one-dimensional search solution is proposed for single-sensor emitter localization based on signal periodicity. By introducing an intermediate variable, this single-sensor localization problem can be solved by solving a set of equations for classic multi-sensor time difference of arrival localization, whose algebraic solutions can be obtained by the well-known two-stage weighted least squares (TSWLS) algorithm. In this manner, the two-dimensional or three-dimensional search for the emitter location can be replaced by a one-dimensional search for the intermediate variable. Simulations indicate that, at the expense of a small loss of localization accuracy, the proposed method achieves a significant advantage in computation time, compared with the conventional maximum likelihood technique.

This paper focuses on passive emitter localization using moving sensors. The increase in observation time is beneficial to improve the localization accuracy, but it could cause deterioration of the relative motion between the emitter and the sensors, especially the nonlinear motion. The common localization algorithms typically have two steps: (1) parameter estimation and (2) position determination, where the parameters are assumed to be constant, and it is not applicable for long observation times. We proposed the time-varying delay-based direct position determination (DPD-TVD) method, regarding the variation in the propagation time delay during the observation time. Using one step, the proposed algorithm can obtain the emitter’s position directly from the received signals by calculating the cost function corresponding to the map grid. By better adapting to highly dynamic scenarios, the proposed algorithm can achieve better localization accuracy than that of constant parameters using one-step or two-step procedures, which is demonstrated by the simulation results.

The optimal implementation for a biologically inspired coupling structure to overcome the limitation of short baseline direction‐finding is determined. This approach is inspired by the Ormia ochracea , a parasitoid insect living in North America. It can locate the crickets’ call accurately with the very small distance between its ears far beyond the accuracy of an interferometer with the same baseline. This outstanding performance depends on the mechanical coupling in its auditory system. The first research focus is on the mechanism of the coupling structure, considering not only the amplification on phase difference but also the effect on output power, which leads to the performance improvement in comparison with the traditional method. Then, the biologically inspired coupling structure is optimised to achieve the best direction‐finding performance in crickets’ sound frequency, reducing the estimation error by 75% when the signal incident at boresight. To implement the actual coupling structure with optimal direction‐finding performance, both the analogue circuit and the digital filter implementation are discussed, and the latter attains the theoretical optimal performance. Finally, a direction‐finding system prototype is carried out to verify the advantage of digitally implemented coupling structure, and the measurement result approximates the corresponding Cramr–Rao lower bound.

Inspired by the Ormia Ochracea hearing mechanism, a new direction of arrival estimation using multiple antenna arrays has been considered in spatially colored noise fields. This parasitoid insect can locate s cricket’s position accurately using the small distance between its ears, far beyond the standard array with the same aperture. This phenomenon can be understood as a mechanical coupled structure existing between the Ormia ears. The amplitude and phase differences between the received signals are amplified by the mechanical coupling, which is functionally equivalent to a longer baseline. In this paper, we regard this coupled structure as a multi-input multi-output filter, where coupling exists between each pair of array elements. Then, an iterative direction-finding algorithm based on fourth-order cumulants with fully coupled array is presented. In this manner, the orientation of the mainlobe can direct at the incident angle. Hence, the direction-finding accuracy can be improved in all possible incident angles. We derive the Cramér-Rao lower bound for our proposed algorithm and validate its performance based on simulations. Our proposed DOA estimation algorithm is superior to the existing biologically inspired direction-finding and fourth-order cumulants-based estimation algorithms.

To eliminate the bottleneck of computation and communication capability in classic direct position determination, recently several fast approximation methods have been proposed. However, the estimation accuracy of these methods is not satisfactory. In this letter, the common theoretical principle behind these fast approximation methods is analysed in depth. It is demonstrated that the maximum eigenvalue of a matrix can be approximated by the matrix norm. The performance of several commonly used matrix norms is then compared, and the Frobenius norm is preferable because of its great potential inferred from the analysis in this letter. Numerical simulations indicate that, compared with conventional methods, the proposed method can achieve better estimation accuracy with less computational complexity.

Radio Frequency Interference (RFI) significantly degrades the quality of spaceborne Synthetic Aperture Radar (SAR) images, and RFI source localization is a crucial component of SAR interference mitigation. Single-station, single-channel SAR, referred to as single-channel SAR, is the most common operational mode of spaceborne SAR. However, studies on RFI source localization for this system are limited, and the localization accuracy remains low. This paper presents a method for locating the ground-based RFI source using spaceborne single-channel SAR echo data. First, matched filtering is employed to estimate the range and azimuth times of the RFI pulse-by-pulse in the SAR echo domain. A non-convex localization model using Pulse Range Difference of Arrival (PRDOA) is established based on the SAR observation geometry. Then, by applying Weighted Least Squares and Semidefinite Relaxation, the localization model is transformed into a convex optimization problem, allowing for the solution of its global optimal solution to achieve RFI source localization. Furthermore, the error analysis on the PRDOA localization model is conducted and the Cramér–Rao Lower Bound is derived. Based on the simulation platform and the SAR level-0 raw data of Gaofen-3, we conduct several verification experiments, with the Pulse Time of Arrival localization selected for comparison. The results demonstrate that the proposed method achieves localization accuracy with a hundred-meter error in azimuth and a kilometer-level total error, with the total localization errors reduced to approximately 1/4 to 1/3 of those of the Pulse Time of Arrival method.