Unmanned aerial vehicle-borne radar calibration system based on time division multiplexing and adaptive edge detection

Abstract

To address the degradation of beam performance in array radars induced by channel amplitude and phase errors, as well as the inadequate flexibility of traditional calibration systems for radars of varying scales, this paper proposes a lightweight, dual-mode collaborative calibration scheme based on an unmanned aerial vehicle (UAV) platform, First, a mobile calibration system seamlessly integrating a transmit/receive (TR) module, a calibration antenna, and a wireless communication module is developed. Second, to ensure efficient transceiver operation and the precise extraction of calibration signals, a time-division multiplexing (TDM) transmission architecture is designed at the transmitting end. Concurrently, a pulse signal detection algorithm based on autocorrelation and adaptive edge detection is proposed at the receiving end. This algorithm effectively mitigates noise interference in complex environments, significantly enhancing both the detection precision and the Time of Arrival (TOA) estimation accuracy of the calibration signals. Finally, system implementation and field experiments demonstrate that the proposed hardware-software architecture and detection algorithm can achieve rapid, high-precision calibration of channel amplitude and phase errors for various array radars. This research provides an innovative, flexible, and efficient mobile calibration solution for radar systems across diverse scales and deployment environments.