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Joint transceiver beamforming is a fundamental and crucial research task in the field of signal processing. Despite extensive efforts made in recent years, the joint transceiver beamforming of frequency diverse array (FDA)-based multiple-input and multiple-output (MIMO) radar has received relatively less attention and is confronted with some tricky challenges, such as range–angle decoupling and the interaction between multiple performance metrics. In this paper, we initially derive the generalized ambiguity function of the FDA-MIMO radar to explore the intrinsic correlation between its waveform design and resolution. Following that, the joint beamforming optimization is formulated as a nonconvex bivariate quadratic programming problem (NBQP) with the aim of maximizing the Signal-to-Interference-Noise Ratio (SINR) of the FDA-MIMO radar system. Building upon this, we introduce an innovative alternating manifold optimization with nested iteration (AMO-NI) algorithm to address the NBQP. By incorporating manifold optimization into iterative updates of transmit waveform and receiving filter, the AMO-NI algorithm considers the interdependencies among the optimization variables. The algorithm efficiently and expeditiously finds global optimum solutions within a finite number of iterations. Compared with other methods, our approach yields a superior beampattern and higher SINR. [ABSTRACT FROM AUTHOR]

The problem of suppressing mainlobe deceptive jammers, which spoof radar systems by generating multiple false targets, has attracted widespread attention. To tackle this problem, in this paper, the multiple-input multiple-output (MIMO) radar system was utilized by applying a quadratic element phase code (QEPC) to the transmitted pulses of different elements. In the receiver, by utilizing the spatial frequency and Doppler frequency offset generated after decoding, the jammers were equivalently distributed in the sidelobes of the joint Doppler-transmit-receive domain and were distinguishable from the true target. Then, further spatial frequency compensation and Doppler compensation were performed to align the true target to the zero point in the transmit spatial and Doppler domains. Moreover, by designing appropriate coding coefficients, the jammers were suppressed by data-independent Doppler-transmit-receive three-dimensional beamforming. However, the beamforming performance was sensitive to angular estimation mismatches, resulting in performance degradation of jammer suppression. To this end, a center-boundary null-broadening control (CBNBC) approach was used to broaden the nulls in the equivalent beampattern by generating multiple artificial jammers with preset powers around the nulls. Thus, the false targets (FTs) with deviations were sufficiently suppressed in the broadened notches. Numerical simulations and theoretical analysis demonstrated the performance of the developed jammer suppression method. [ABSTRACT FROM AUTHOR]

A joint radar-communication (JRC) system utilizes the integrated transmit waveform and a single platform to perform radar and communication functions simultaneously. Admittedly, the multibeam waveform design approach could transmit the assigned waveforms in different beams with the aid of spatial and temporal degrees of freedom. However, a high sidelobe level (SLL) in the beampattern reduces energy efficiency and expands exposure probability. In this study, we propose a novel spatial–temporal joint waveform design method based on the beamforming algorithm to form a low SLL beampattern. Waveform synthesis constraints are considered to synthesize desired radar and communication waveforms at designated directions. Furthermore, we impose the constant modulus constraint to lessen the impact of the high peak-to-average ratio (PAPR). The optimization process of the whole model can be summarized as two stages. First, the covariance matrix is created by convex optimization with respect to the minimum SLL. Second, the integrated transmit waveform is tuned through an alternating projection algorithm. Based on the simulation findings, we demonstrate that the proposed method outperforms the traditional methods in terms of low SLL and waveform synthesis. Meanwhile, we validate the effectiveness of the proposed method using semi-physical experiment results. [ABSTRACT FROM AUTHOR]

In this paper, the problem of mainlobe deceptive jammer suppression is solved with the frequency diversity array-multiple-input multiple-output (FDA-MIMO) radar system. At the modeling stage, based on the FDA-MIMO radar, a quadratic phase code (QPC) is applied along the slow time dimension in the transmit array. In the receiver, after decoding and principal range compensation, the true and false targets that are generated in an identical angle, can be discriminated in the joint transmit-receive-Doppler frequency domain. Particularly, the false targets are equivalently moved from the mainlobe to the sidelobes in the transmit spatial frequency domain. Then, by performing the data-dependent transmit-receive-Doppler three-dimensional beamforming, the false targets are suppressed owing to Doppler and range mismatches. Moreover, by moving the jammers to nulls in the Doppler frequency domain, the capability in terms of the maximum number of suppressible jammers can be strengthened with an appropriate coding coefficient and frequency increment. Numerical results can certify the suppression capability of the QPC-FDA-MIMO radar. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]