Multiple-input multiple-output(MIMO)technology significantly improves the azimuth resolution of high-frequency surface wave radar.However

the ubiquitous amplitude-phase errors in the transmit and receive arrays cause virtual array manifold ambiguity

thereby degrading the estimation accuracy of the direction of arrival(DOA).To address the error decoupling problem of existing self-calibration algorithms in MIMO high-frequency surface wave radar systems

a step-by-step alternating optimization angle measurement algorithm based on the eigen-subspace is proposed in this paper.The algorithm utilizes the signal power constraints of the transceiver channels to pre-calibrate the amplitude errors

and subsequently employs the Lagrange multiplier method to perform step-by-step alternating optimization on the DOA and the transceiver amplitude-phase errors

achieving high-precision and robust angle measurement in the presence of transceiver array errors.Numerical simulations and measured data from the Wuhan University AMR high-frequency surface wave radar system demonstrate that the proposed algorithm can effectively overcome the array manifold ambiguity caused by amplitude-phase errors.It significantly reduces the root mean square error(RMSE)of DOA estimation and exhibits exceptionally high angle measurement accuracy and robustness.