Target localization with unambiguous range and angle estimation of the signal-of-interest is a key task of a radar system, especially for wide region surveillance. In this article, we develop a novel dual-mode array radar scheme, namely phased array and frequency diverse array cooperated radar, to provide unambiguous range and angle estimation. Our approach combines the advantages of the PA in high transmit gain and that of the FDA in resolving range ambiguity. In general, two kinds of cooperative parameter estimation algorithms are derived to determine the range and angle parameters jointly. The proposed algorithms can be interpreted as different combination methods of the PA and FDA, including the uniform combination and weighted combination based on weighted least squares, where the weight is designed with user tunable angle parameters. Particularly, the design criterion for the tunable parameter is given. At the analysis stage, the Cramér–Rao bounds are studied to verify the performance of parameter estimation. Extensive simulation results demonstrate the effectiveness of parameter estimation with the dual-mode array radar.

High-resolution and wide-swath (HRWS) imaging serves as an important task for synthetic aperture radar (SAR). However, the trade-off between high azimuth resolution and wide unambiguous swath coverage has not been well optimized in traditional SAR system. Meanwhile, the ultra-wideband signal is required to obtain ultra-high range resolution imaging. It is not easy to increase the bandwidth directly due to the difficulty of system design. To this end, this work makes notable contribution on a sub-band frequency diverse array framework to realize range ambiguous echoes separation and wideband signal synthesis from narrowband signals. By introducing a small frequency increment across the elements within each subarray, the transmit steering vector within each subarray is range-angle-dependent, making it feasible to resolve range ambiguity in the spatial frequency. In addition, the transmitted waveforms of different subarrays occupy different frequency bands in range frequency domain, which play a pivotal role in achieving high resolution imaging. With phase compensation and sub-band frequency spectrum splicing technique, the wideband signal can be obtained. Simulation results have verified the effectiveness of the proposed approach.

Forward-looking mode for moving target detection is important for airborne radar systems, however, it is difficult to suppress the range-dependent clutter in the presence of range ambiguity using the traditional space-time adaptive processing (STAP) techniques. In this paper, a vertical coherent frequency diverse array (FDA) radar using quadratic phase coding (QPC) is proposed to alleviate the range-ambiguous clutter problem. The proposed vertical coherent FDA radar has two major advantages: i) it uses an identical baseband waveform for each transmit element, which prevents the unreal orthogonal waveform assumption in multiple-input multiple-output (MIMO) framework; ii) it achieves wide spatial coverage in elevation within a single pulse duration, which is desirable for the airborne reconnaissance radar. The space-frequency coupled characteristic of vertical coherent FDA is revealed and a series of 2-dimensional (2-D) matched filters are designed, which is helpful for range-ambiguous clutter separation. Based on the QPC technique, the residual clutter is suppressed by orthogonal projection (OP) filtering, which further improves the target detection performance. With the proposed vertical coherent FDA using QPC, the range-ambiguous clutter can be separated successfully, and the clutter suppression performance is improved. Simulation results are presented to verify the effectiveness of the proposed method in serious range-ambiguous clutter scenarios.

This paper propose a cognitive FDA-MIMO radar network (CFDA-MIMON) target discrimination and tracking algorithm under main-lobe deceptive trajectory interference. This algorithm can be divided into two stages: search-discrimination-initialization and cognitive target tracking. The first stage mainly uses the distribution characteristics of target and main-lobe deceptive trajectory interference on different radars to discriminate the target and interference in the radar network. A target state initialization strategy driven by G-pair measurements with large time interval is proposed for target tracking. In the second stage, a cognitive target tracking algorithm of single FDA-MIMO radar system is designed based on the criteria of maximum Capon power spectrum (CMCP). In addition, in order to avoid the divergence problem of the EKF filter, a target state correction method (TSC) based on auxiliary particles is proposed. Finally, the fusion strategy of multiple radar trajectories is used to alleviate the estimation error of the single radar. Numerical experiments verify that the proposed CFDA-MIMON target discrimination and tracking algorithm can distinguish the target from main-lobe deceptive trajectory interference without prior information of the target, and output the target's trajectory.

A range-ambiguous clutter suppression approach based on extended azimuth phase coding (EAPC) is proposed to handle the range ambiguity of the multiple-input multiple-output synthetic aperture radar (MIMO-SAR) system for ground moving target indication (GMTI) application. The echoes from different ambiguous range regions can be well separated in the transmit spatial frequency domain by properly designing the EAPC shift factor. In the sequel, a set of transmit filters are employed to extract the echoes of each ambiguous region independently. Then the azimuth deramp operation is applied to the extracted data to focus the target energy of the desired region while the residual target energy of other regions is still smeared due to the mismatched reference function. After this, the adaptive matched filtering algorithm is adopted to suppress the clutter and detect the moving target. Finally, numerical simulation experiments are presented to demonstrate that the developed framework can obtain good results for range-ambiguous clutter suppression and ground moving target detection.