Frequency diverse array multiple-input multiple-output (FDA-MIMO) communication regime has received a lot of attention in the field of point-to-point communication and interference suppression due to its degrees of freedom in the range domain. Previous researches have mainly considered non-coherent source scenarios. However, FDA-MIMO communication system in low-elevation is subject to multipath effects in addition to the potential threats within the mainlobe. The discrimination of true and false targets using meter-wave FDA-MIMO radar in low-elevation scenarios is still a problem that needs to be addressed. This letter mainly derives the signal model of the mainlobe deceptive jamming acting on the meter-wave FDA-MIMO radar and proposes a method for the discrimination of true and false targets. Simulation results verify the effectiveness of the proposed method.

Frequency diverse array multiple-input multiple-output (FDA-MIMO) radar has received a lot of attention due to the advantages of waveform diversity. Suppression of mainlobe deceptive jamming can be effectively achieved with the degree of freedom (DOF) in the range domain. However, the existing research mainly focuses on non-coherent signals. The echo signal of VHF-FDA-MIMO radar for low elevation has its own unique characteristics. False targets cannot be suppressed with conventional beamforming methods. Thus, a signal model for VHF-FDA-MIMO radar subjected to deceptive jamming is established. The reconstruction of the covariance matrix and the estimation of the steering vector are implemented with the generalized MUSIC algorithm. In addition, a matching Capon reconstruction method is proposed to finish the robust suppression of false targets for the problem of self-cancellation in the absence of a priori information. Finally, the beampattern and performance curves of different methods are compared. The simulation results show that the methods can be effectively applied to the suppression of deceptive jamming in VHF-FDA-MIMO radar under the multipath effect.

This paper proposes two data-independent phase-only beamforming algorithms for frequency diverse array multiple-input multiple-output radar against swarm interference. The proposed strategy can form a deep null at the interference area to achieve swarm interference suppression by tuning the phase of the weight vector, which can effectively reduce the hardware cost of the receiver. Specifically, the first algorithm imposes constant modulus constraint and sidelobe level constraint, and the phase-only weight vector is solved. The second algorithm performs a constant modulus decomposition of the weight vector to obtain two phase-only weight vectors, and uses two parallel phase shifters to synthesize one beamforming weight. Both methods can obtain the phase-only weight to realize suppression for swarm interference. Simulation results demonstrate that our strategy shows superiority in beam shape, output signal-to-interference-noise ratio, and phase shifter quantization performance, and has the potential for use in many applications, such as radar countermeasures and electronic defense.

This letter proposes an iterative, fast, and efficient single-snapshot range and angle estimation method for frequency diverse array multiple-input multiple-output radar. The proposed approach transforms the angle and range estimation problem into the transmit and receive frequency estimation, and a two-dimensional frequency estimation algorithm is designed for multiple sinusoids (corresponding to multiple targets in radar). The frequency estimation is divided into coarse estimation and fine estimation. The coarse estimation can be achieved by using the Discrete Fourier Transform, and the fine estimation is estimated by the designed iterative structure. The designed algorithm achieves effective target parameters estimation with low computational cost. Simulation results demonstrate the effectiveness of the algorithm under various situations.