Reliable Doppler Estimation in Asynchronous Moving ISAC Devices via IMU Integration

Abstract

We present an Integrated Sensing And Communication (ISAC) framework for the joint estimation of the Doppler frequency of a passive mobile target in a bistatic scenario with clock-asynchronous nodes and where the Receiver (RX) is static but the Transmitter (TX) is mobile. In such a setup, previous geometric solutions are integrated with an Inertial Measurement Unit (IMU) device at the TX, coming up with a truly joint data fusion and estimation algorithm based on extended Kalman filtering. The approach jointly estimates the target Doppler frequency, along with the speed and direction of motion of the TX and it is robust to the unavailability of static paths between the TX and RX pair, a condition that makes previous solutions ineffective. The developed extended Kalman filter strikes a balance between the accuracy of ISAC and the IMU reliability. The proposed solution is validated via numerical simulations, obtaining a median Doppler error of 1.2% with a smartphone-grade IMU under realistic operating conditions.