The essence of amplitude-modulation based dual-function radar-communications is to modulate the sidelobe of the transmit beampattern while keeping the main beam, where the radar function takes place, unchanged during the entire processing interval. The number of distinct sidelobe levels (SLL) required for information embedding grows exponentially with the number of bits being embedded. We propose a simple and computationally cheap method for transmit beampattern synthesis which requires designing and storing only two beamforming weight vectors. The proposed method first designs a principal transmit beamforming weight vector based on the requirements dictated by the radar function of the DFRC system. Then, a second weight vectors is obtained by enforcing a deep null towards the intended communication directions. Additional SLLs can be realized by simply taking weighted linear combinations of the two available weight vectors. The effectiveness of the proposed method for beampattern synthesis is verified using simulations examples.
Recently, dual-function radar-communications (DFRC) has been proposed as means to mitigate the spectrum congestion problem. Existing amplitude-shift keying (ASK) methods for information embedding do not take full advantage of the highest permissable sidelobe level. In this paper, a new ASK-based signaling strategy for enhancing the signal-to-noise ratio (SNR) at the communication receiver is proposed. The proposed method employs one reference waveform and simultaneously transmits a number of orthogonal waveforms equals to the number of 1's in the binary sequence being embedded. 3 dB SNR gain is achieved using the proposed method as compared to existing sidelobe ASK methods. The effectiveness of the proposed information embedding strategy is verified using simulations examples.
Two-dimensional (2D) transmit beamforming aims at focusing the transmitted energy within certain desired sector while minimizing the amount of energy in the out-of-sector regions. In this paper, we propose parsimonious formulations to the sidelobe control problem in 2D transmit beamforming with multidimensional arrays. The out-of-sector region is partitioned into a small number of subsectors where the subspace spanned by the steering vectors associated with the spatial directions within a certain subsecetor is approximated by the effective discrete- prolate spheroidal sequences associated with that subsector. Then, the sidelobe control is achieved by imposing constraints on the magnitude of the inner product between the 2D transmit beamforming weight vector and the discrete-prolate spheroidal sequences. Simulations examples are presented which show the effectiveness of the proposed formulations.
We consider the problem of single snapshot direction-of-arrival (DOA) estimation of multiple targets in monostatic multiple-input multiple-output (MIMO) radar. When only a single snapshot is used, the sample covariance matrix of the data becomes non-invertible and, therefore, does not permit application of Capon-based DOA estimation techniques. On the other hand, low-resolution techniques, such as the conventional beamformer, suffer from biased estimation and fail to resolve closely spaced sources. In this paper, we propose a new Capon-based method for DOA estimation in MIMO radar using a single radar pulse. Assuming that the angular locations of the sources are known a priori to be located within a certain spatial sector, we employ multiple transmit beams to focus the transmit energy of multiple orthogonal waveforms within the desired sector. The transmit weight vectors are carefully designed such that they have the same transmit power distribution pattern. As compared to the standard MIMO radar, the proposed approach enables transmitting an arbitrary number of orthogonal waveforms. By using matched-filtering at the receiver, the data associated with each beam is extracted yielding a virtual data snapshot. The total number of virtual snapshots is equal to the number of transmit beams. By choosing the number of transmit beams to be larger than the number of receive elements, it becomes possible to form a full-rank sample covariance matrix. The Capon beamformer is then applied to estimate the DOAs of the targets of interest. The proposed method is shown to have improved DOA estimation performance as compared to conventional single-snapshot DOA estimation methods.