An algebraic approach for joint estimation of time-frequency offsets and target parameters in distributed MIMO radar systems

Distributed multiple-input multiple-output (MIMO) radar systems exhibit significant advantages in target detection and localization through spatial diversity and anti-jamming capabilities. However, practical deployment faces challenges due to time-frequency synchronization errors caused by non-ideal hardware and complex electromagnetic environments. This paper addresses the joint estimation problem of time-frequency offsets and target parameters in distributed MIMO radar systems by proposing a novel algebraic solution. The method adopts a two-stage weighted least squares (TSWLS) framework: In the first stage, bistatic range (BR) and range rate (BRR) measurements are transformed into pseudolinear equations to derive initial estimates of the target's position and velocity. Subsequently, an iterative refinement process constructs new pseudolinear formulations via observation equations to enhance parameter accuracy while simultaneously resolving time-frequency synchronization errors. Theoretical analysis demonstrates that the proposed algorithm achieves near-unbiasedness under low-noise conditions and attains the Cramér-Rao lower bound (CRLB). Numerical simulations confirm its superiority over existing methods.