Linearization Optimization of Amplitude-Comparison Curve for High-Accuracy Direction Finding in Passive Radar

In the signal processing workflow of passive radar, considering the requirements of real-time processing for radar systems, amplitude-comparison based direction finding is mostly adopted for target angle estimation, although this method suffers from low angle estimation accuracy. The direction estimation accuracy degrades sharply when the target deviates far from the beam center, entering the sidelobe region or the beam edge i.e., the low-slope region. Adjacent beams are usually designed to intersect at a level slightly below the beam peak (e.g., 3 dB). However, in order to cover a large angle monitoring range, multiple beams must be spliced together, yet the direction finding performance in the splicing region is always inferior to that in the central region, which impairs effective angle estimation for weak targets and further degrades the accuracy of target tracking performance. To address these issues, this paper proposes an amplitude-comparison curve based direction finding method using multi-objective optimization, which takes the linearity of the amplitude-comparison curve as the optimization objective to reduce the number of beams required for coverage while improving direction finding accuracy.