Abstract: A method for jointly estimating gain-phase error and direction of arrival (DOA) based on an unmanned aerial vehicle (UAV) array includes: equipping each UAV with an antenna, and forming a receive array through a swarm of multiple UAVs to receive source signals; when an observation baseline of the swarm remains unchanged, changing array manifold through movement of the UAVs, and re-sensing the source signals; for each sensed source signals, calculating a covariance matrix, and obtaining a corresponding noise subspace through eigenvalue decomposition; and constructing a quadratic optimization problem based on the noise subspace and array steering vector, constructing a cost function, and implementing joint estimation of the gain-phase error and the DOA through spectrum peak search. The method can jointly estimate the DOA and gain-phase error and calibrate the gain-phase error, thereby improving accuracy of passive positioning.

Abstract: A method for jointly estimating gain-phase error and direction of arrival (DOA) based on an unmanned aerial vehicle (UAV) array includes: equipping each UAV with an antenna, and forming a receive array through a swarm of multiple UAVs to receive source signals; when an observation baseline of the swarm remains unchanged, changing array manifold through movement of the UAVs, and re-sensing the source signals; for each sensed source signals, calculating a covariance matrix, and obtaining a corresponding noise subspace through eigenvalue decomposition; and constructing a quadratic optimization problem based on the noise subspace and array steering vector, constructing a cost function, and implementing joint estimation of the gain-phase error and the DOA through spectrum peak search. The method can jointly estimate the DOA and gain-phase error and calibrate the gain-phase error, thereby improving accuracy of passive positioning.