Modelling the clutter with accurate spatialtemporal correlation, amplitude statistical characteristic and coherence is significant to the evaluation of constant false alarm rate (CFAR) detection performance for coherent radar seeker in clutter. In this study, the authors propose a modelling method for spatialtemporal correlated coherent K distributed clutter. At first, with the assumption that clutter shape parameter is known, the authors estimate the scale parameter of K distributed clutter by calculating the clutter power of the range reference cell of CFAR detection according to the radar seeker operating circumstance. Then, they model the temporal correlated coherent K distributed clutter and spatial correlated coherent K distributed modulation component, respectively, by employing exogenous modelling method. The authors propose to modulate the temporal clutter with spatial modulation sequence to obtain spatialtemporal correlated coherent K distributed clutter for multiple range reference cells of CFAR detection. Finally, they show the validity of the proposed modelling method by simulation.

Time reversal has attracted considerable research interest because of its potential for signal enhancement. In the past, target focusing and reverberation nulling are separately investigated as two complementary aspects of time-reversal processing. In essence, nulling is regarded as one kind of focusing with minimising the energy incident on a location. When time-reversal operation is regarded as inversed beamforming, it is available to simultaneously realise time-reversal focusing and nulling under an optimum beamforming framework. The feasibility of the combination processing is evaluated in detection of a small target in the presence of strong reverberation. The acoustic energy focused on a target of interest is maintained constant while reverberation is regarded as an interference to be suppressed by the nulling technique. The experimental results have verified the effectiveness of optimum time-reversal processing for active target detection in a shallow water environment.

This study presents two alternative techniques for the estimation of the target direction of arrival (DOA) for a moving radar equipped with digital beamforming, operating in look-down against strong clutter echoes. Both the considered techniques, namely AB space–time adaptive processing (AB-STAP) and generalised monopulse estimator, are based on a dual cancelled channel approach that simplifies their implementation. An extensive performance comparison is presented for the ground moving targets. Both the theoretical and simulated analyses of DOA estimation are performed, which include the comparison to the Cramér-Rao bound. The considered processing schemes are shown to yield comparable accuracies in target DOA estimation with respect to a maximum likelihood estimator. Moreover, they ensure lower computational cost, since no numerical maximisation of any functional is required. AB-STAP shows the additional nice property of estimation robustness when a limited set of homogeneous data is available to achieve the adaptivity. The comparison is finally performed applying the different estimators to a set of real multichannel data.

Channel balancing is one of the crucial steps to obtain a satisfactory result in multichannel moving target detection. Therefore many algorithms have been proposed to realise channel balancing in multichannel synthetic aperture radar (SAR)-ground moving target indication (GMTI) systems, such as an adaptive two-dimensional calibration algorithm, linear fitting algorithm and eigen-decomposition algorithm. However, all of these aforementioned algorithms have some small defects in certain conditions, when used in the real data of multichannel wide area surveillance (WAS)–GMTI systems. The small defects can increase the false alarm probability, which is undesirable in moving target detection. In this study, after the detailed analysis about the interference phase in the wide-area surveillance mode, a novel channel balancing algorithm is proposed to perform channel balancing in multichannel WAS–GMTI systems. The new algorithm mainly concentrates on the balancing of systematic azimuthal phase errors. The effectiveness of the proposed algorithm is demonstrated when compared with other typical channel balancing algorithms in Monte Carlo simulations and real data processing.

The high-speed movement of a target may cause range migration and Doppler frequency migration of the radar echo, which has a serious impact on the detection performance of the radar. To resolve the problem of detecting a high-speed target in linear frequency modulation radar, this study analyses the effect on the integration gain caused by range migration and Doppler frequency migration, and proposes a corresponding compensation method according to the different input signal-to-noise ratios (SNRs) of the echo signal. To compensate for range migration in high SNRs, two-dimensional median filtering and constant false alarm rate technology are combined to estimate the speed. For low SNRs, based on coarse valuations, the authors use the discrete Fourier transformation (DFT) to realise the fractional delay cell to improve speed accuracy. Furthermore, to compensate for Doppler frequency migration, an instantaneous cross-correlation method is proposed for high SNRs, which is combined with the fractional Fourier transform method to estimate the acceleration for low SNRs. The input SNR threshold for the different algorithms is then analysed using simulation data, and the theoretical reference value is shown. Finally, the study verifies the effectiveness of the proposed methods through simulation and measured data.

This study deals with the problem of adaptive detection in the presence of signal mismatch. An effective parametric detector is proposed, which encompasses Kelly's generalised likelihood ratio test (GLRT), adaptive matched filter (AMF) and adaptive beamformer orthogonal rejection test (ABORT) as its three special cases. The novel detector can control the degree to which the mismatched signals are rejected. A remarkable feature is that the novel detector can achieve slightly higher probability of detection, for matched signals than those of Kelly's GLRT, AMF and ABORT. Furthermore, it can also provide both improved robustness to the mismatched signals and enhanced rejection of the mismatched signals than its natural competitors.

The independence of the process and observation noises is the prerequisite of many Kalman-type filters. However, the fact is that these two noises may be correlated with each other in actual applications. The filtering of the non-linear systems with cross-correlated process and observation noises at the same epoch is studied. First, a decorrelated scheme is introduced and a pseudo non-linear process equation is reconstructed in which the corresponding pseudo process noise is no longer cross-correlated with the observation noise; so a celebrated non-linear filter, that is, the unscented Kalman filter (UKF) can be used to filter the non-linear problem. Second, the (conditionally) linear substructure in the above non-linear system is exploited and a refined filter called marginal UKF is employed so as to reduce computational load without deteriorating the accuracy. The performance of the standard UKF for the original system equations, the standard and marginal unscented UKFs for the reconstructed system equation are compared in the simulation. From the results of the simulation, the theoretical statements are validated, and some interesting but not surprising phenomena are also founded, that is, the performance of the conventional filter actually does not degenerate, whereas that of the proposed filters become better when cross-correlation exists and increases. This phenomenon can be due to the fact that the proposed filters exploited the extra information buried in the cross-correlation, whereas the conventional filter fails to do so.

For some critical static applications of Global Navigation Satellite Systems (GNSS), such as monitoring station and reference station in the GNSS control segment, multipath error shows regular fading characteristics related to satellite orbit type. However, for Geostationary Earth Orbit (GEO) satellites, observations under different systems show great diversity, the regularity of the multipath fading characteristic for GEO satellite is not apparent, and the reason is not clear as these observations can be influenced by various factors. To know the reason and the mechanism of these differences is very important for GNSS system building and monitoring, especially for the control segment, one major function of which is monitoring the whole system states and ensuring the system reliability. To explain the differences among these observations, a theoretical analysis about the satellite orbit influence on multipath fading is made in this study. The analysis is based on a proposed factor named orbit multipath fading factor, which can reflect the orbit influence independent from the uncontrolled environment factors. The analysis result shows that for GEO satellites, the multipath fading frequency varies large with time, and is very sensitive to orbit inclination, which can well explain the various fading characteristics actually observed in theory.