A Signal-level Fusion Distributed Radar Localization Method Based on Wideband Synthesis Technology - Zhang, Wentao; Miao, Chen; Ma, Yue; Wu, Wen (IEEE sensors journal, 2023)
Traditional distributed radar systems face challenges like limited localization precision and stringent time synchronization demands in implementing signal-level fusion algorithms. This paper presents a novel distributed radar localization method based on wideband signal synthesis technology to address these issues. In this method, each node of the distributed radar simultaneously transmits a set of narrowband stepped linear frequency-modulated signals. After de-chirping and filtering separation, the echo signals from each node are calibrated and synthesized into an equivalent wideband signal. This process improves the range resolution and localization accuracy of single nodes. However, wideband synthesis necessitates precise distance data, and the estimation error from narrowband echoes can be substantial, affecting the synthesis's efficiency. To overcome this, we propose a grid search wideband synthesis algorithm. The algorithm establishes a search area centered on the distance estimation derived from the narrowband signals, with a diameter determined by the resolution of these signals. Within this search area, the algorithm conducts a grid search, utilizing the peak magnitude of the synthesized signal's Fast Fourier Transform spectrum as a criterion to find the most accurate synthesis result. This method can be integrated with traditional fusion algorithms, enhancing localization precision further. Theoretical analysis and simulation results demonstrate that our method outperforms conventional techniques in terms of localization accuracy. Notably, the grid search algorithm reduces the requirement for precise time synchronization in signal-level fusion algorithms, improving the method's adaptability.