Unified Near-Field and Far-Field TDOA Direction-Finding with Systematic Uncertainties

This paper focuses on reducing the effect of systematic uncertainties on the near-field or far-field source direction-finding accuracy by introducing a calibration emitter, which suffers the same uncertainties as the actual source. We propose a modified polar representation (MPR)-based closed-form algebraic algorithm, i.e., the improved successive unconstrained minimization (SUM), to eliminate the common errors of time difference of arrival (TDOA) measurements, thereby refining the source direction-finding accuracy. The simulations show that the proposed algorithm can approach the Cramer-Rao Lower Bound (CRLB); and demonstrate the positive effect of the calibration emitter on the direction-finding performance under the condition of varying measurement error, source range, and sensor position error.