Suppression of radar-to-radar jammers, especially the mainbeam jammers, has been an urgent demand in vehicular sensing systems with the expected increased number of vehicles equipped with radar systems. This paper deals with the suppression of mainbeam deceptive jammers with frequency diverse array (FDA)-multiple-input multiple-output (MIMO) radar, utilizing its extra degrees-of-freedom (DOFS) in the range domain. At the modelling stage, false targets, which lag several pulses behind the true target, are considered as a typical form of mainbeam jammers. To this end the data-independent beamforming is performed to suppress false targets by nulling at the equivalent transmit beampattern with an appropriate frequency increment. However, the suppression performance degrades in the presence of transmit spatial frequency mismatch, which could be induced by quantization errors, angle estimation errors and frequency increment errors. To solve this problem, a preset broadened nulling beamformer (PBN-BF) is proposed by placing artificial interferences with appropriate powers around the nulls of the equivalent transmit beampattern. In such a way, effective suppression of deceptive jammer can be guaranteed owing to the broadened notches. At the analysis stage, numerical results in a scenario with multiple unmanned aerial vehicles (UAVs) are provided to illustrate the effectiveness of the devised data-independent BF, and the signal-to-interference-plus-noise ratio is improved compared with the conventional data-independent BF.

This paper deals with the problem of adaptive target detection in the presence of homogeneous Gaussian interference with frequency diverse array multiple-input multiple-output (FDA-MIMO) radar. Adaptive detectors are devised according to the generalized likelihood ratio test (GLRT) criterion, where the position of the target within each range cell is assumed unknown. To obtain the maximum likelihood (ML) estimate of the target incremental range under the H1 hypothesis, three different optimization strategies are pursued. They are respectively based on Semi-definite programming (SDP), discrete grid search, and Newton-method. At the analysis stage, a detection performance comparison is carried on among the new proposed adaptive detectors, benchmark and mismatched receivers. Numerical results corroborate the effectiveness of the developed receivers.

Unlike the conventional phased array, the frequency-diverse array (FDA) employs a tiny frequency increment across the array elements, which is capable of providing range–angle–time-dependent beampattern, and thereby offers potential benefits in target localization and interference mitigation. Reported literature on FDA mostly focuses on its intrapulse (fast-time) property and ignores the interpulse (slow-time) feature induced by frequency offset. In this article, incorporating the neglected inherent slow-time coding feature, a novel slow-time FDA multiple-input multiple-output (FDA-MIMO) technique is proposed for the space-time adaptive processing (STAP) radar. The new coding scheme can separate transmitting (Tx) signals via slow-time Doppler filtering, and the problem of signal aliasing is tackled by appropriately designing the slow-time codes. At the receiving (Rx) side, two Rx schemes are devised for recovering range-dependent Tx degrees-of-freedom. Moreover, the relevant clutter rank and the rule for code design are derived in detail. The outstanding merits of the proposed slow-time FDA-MIMO STAP radar consist of the following: There is no specific restriction on the probing waveform; the negative effect of time-variant pattern is perfectly eliminated; and both the target localization accuracy and clutter suppression performance are superior over the state-of-the-art FDA radar systems. Numerical results corroborate the superiorities of the proposed waveform strategy for STAP application.

In this paper, we propose a novel radar framework, referred to as multiple-input multiple-output (MIMO) radar with element-pulse coding (EPC). The EPC employs Fourier basis in joint transmit elements and pulses, which has the advantages of simplicity and convenience for practical realization. It is shown that the EPC-MIMO radar is advantageous in discriminating different pulses and resolving range ambiguity. The discrimination of different pulses is achieved in the transmit spatial frequency domain, and the identifiability of range ambiguity increases with the transmit element number of the radar. Moreover, coherent processing in Doppler domain can be performed after decoding. The coding and decoding procedures are closely related though they are performed in transmitter and receiver, respectively. As the EPC-MIMO radar is capable of resolving range ambiguity, an enhanced parameter estimation approach is developed to obtain the angle and range region number estimates of target. The parameter estimation performance is assessed by the Cram\'er-Rao bound, which reveals useful and interesting findings. Simulation examples are provided to verify the signal properties in EPC-MIMO radar and to demonstrate its superiority in resolving range ambiguity over existing systems.

One-bit radar, performing signal sampling and quantization by a one-bit ADC, is a promising technology for many civilian applications due to its low-cost and lowpower consumptions. In this paper, problems encountered by one-bit LFMCW radar are studied and a two-stage target detection method termed as the dimension-reduced generalized approximate message passing (DR-GAMP) approach is proposed. Firstly, the spectrum of one-bit quantized signals in a scenario with multiple targets is analyzed. It is indicated that highorder harmonics may result in false alarms (FAs) and cannot be neglected. Secondly, based on the spectrum analysis, the DR-GAMP approach is proposed to carry out target detection. Specifically, linear preprocessing methods and target predetection are firstly adopted to perform the dimension reduction, and then, the GAMP algorithm is utilized to suppress high-order harmonics and recover true targets. Finally, numerical simulations are conducted to evaluate the performance of one-bit LFMCW radar under typical parameters. It is shown that compared to the conventional radar applying linear processing methods, one-bit LFMCW radar has about 1:3 dB performance gain when the input signal-to-noise ratios (SNRs) of targets are low. In the presence of a strong target, it has about 1:0 dB performance loss.