A two-stage blind adaptive anti-jamming algorithm for global positioning systems (GPS) is proposed in this study. The new algorithm cancels interferences by projecting the array received signals on the orthogonal complement space of interferences. Then the algorithm utilises the CLEAN method to estimate direction of arrivals of GPS signals according to the period repetitive feature of GPS coarse/acquisition (C/A) code and form the multi-beam, where each beam can point one GPS signal. Test data and simulation results show the effectiveness of the new algorithm.

Unmanned aerial vehicle (UAV) synthetic aperture radar (SAR) is very important for battlefield awareness. For SAR systems mounted on a UAV, the motion errors can be considerably high due to atmospheric turbulence and aircraft properties, such as its small size, which makes motion compensation (MOCO) in UAV SAR more urgent than other SAR systems. In this paper, based on 3-D motion error analysis, a novel 3-D MOCO method is proposed. The main idea is to extract necessary motion parameters, i.e., forward velocity and displacement in line-of-sight direction, fromradar raw data, based on an instantaneous Doppler rate estimate. Experimental results show that the proposed method is suitable for low- or medium-altitude UAV SAR systems equipped with a low-accuracy inertial navigation system.

Space-time adaptive processing (STAP) is an effective method for detecting moving target in airborne/ spaceborne radar. However, the detection of fast air moving targets from high speed platform is challenged by the range walk of both the clutter and moving targets. It is well known that keystone formatting can be used to compensate for the range walk of multiple moving targets simultaneously without using the knowledge of the motion parameters. However, in the presence of serious Doppler ambiguity of fast air moving targets, distribution of the clutter will be affected by the keystone formatting matched to the ambiguity number of targets, and as a result the STAP performance will degrade. In this paper, a novel STAP method is proposed for the detection of fast air moving targets from high speed platform, which can deal with the range walk of both clutter and targets. Effectiveness of the new method is verified via simulation examples.

High-resolution inverse synthetic aperture radar (ISAR) imaging and recognition of ship target is very important for many applications. Although the principle of ISAR imaging of ship target on the sea is the same as that of flying target in the sky, the former usually has more complex motion (fluctuation with the oceanic waves) than the latter, which makes the motion compensation very difficult. However, the change in phase chirp rate caused by the complex motion of ships will deteriorate the azimuth focusing quality. In this paper, we first model the complex motion of ship target with cubic phase terms (parameterised on chirp rate and its change rate), then a new ISAR imaging method, referred to as TC-DechirpClean, is proposed, which estimates the chirp rate and the change rate of chirp rate of all scatters in the time– chirp distribution plane. Both numerical and experimental results are provided to demonstrate the performance of the proposed method.