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Aperture-level simultaneous transmit and receive (ALSTAR) attempts to utilize adaptive digital transmit and receive beamforming and digital self-interference cancellation methods to establish isolation between the transmit and receive apertures of the single-phase array. However, the existing methods only discuss the isolation of ALSTAR and ignore the radiation efficiency of the transmitter and the sensitivity of the receiver. The ALSTAR array design lacks perfect theoretical support and simplified engineering implementation. This paper proposes an adaptive random group quantum brainstorming optimization (ARGQBSO) algorithm to simplify the array design and improve the overall performance. ARGQBSO is derived from BSO and has been ameliorated in four aspects of the ALSTAR array, including random grouping, initial value presets, dynamic probability functions, and quantum computing. The transmit and receive beamforming carried out by ARGQBSO is robust to all elevation angles, which reduces complexity and is conducive to engineering applications. The simulated results indicate that the ARGQBSO algorithm has an excellent performance, and achieves 166.8 dB of peak EII, 47.1 dBW of peak EIRP, and −94.6 dBm of peak EIS with 1000 W of transmit power in the scenario of an 8-element array.

The aperture-level simultaneous transmit and receive (ALSTAR) system uses full digital architecture with an observation channel to achieve remarkably effective isotropic isolation (EII). However, the number of observation channels must be the same as the number of transmit channels, which increases the system’s complexity. To balance the system cost and performance of the ALSTAR, this paper proposes a joint design of sparse arrays and beamforming, which are achieved by a genetic algorithm and an alternating optimization algorithm, respectively. In the sparse design, we introduce beamforming technology to guarantee the EII while decreasing the corresponding elements of observation channel that contribute slightly to the EII. The simulation results are presented for a 32-element array that achieves 185.87 dB of the EII with 1000 W of transmit power. In the cases of sparsity rates at 0.875 and 0.75 (≥0.6), i.e., the number of observation channels decreases by 12.5% (2/16) and 25% (4/16), the reductions in EII do not exceed 1 dB and 3 dB, respectively. However, the EII decreases rapidly with a sparsity rate less than 0.25. Results demonstrate that our proposed joint design of sparse arrays and beamforming can reduce the system cost with little performance loss of EII.

The simultaneous transmit and receive (STAR) system needs to establish sufficiently high isolation between the transmitter and the receiver in order to play its role. However, due to the nonlinear characteristics and the accompanying noise of the active devices in the system, the coupling from the transmit channel to the receive channel cannot be accurately estimated in massive arrays, making it hard to improve the isolation between the transmit and receive channels. This paper proposes a new method to enhance isolation for aperture-level transmitting array and receiving array. The method uses the transmit and receive beamforming technology and aperture optimization technology to enhance the isolation between the transmitting aperture and the receiving aperture. The experimental results show that when the transmit power of an 8-element Vivaldi array is 30 W, the effective isotropic isolation (EII) peak value reaches 153.9 dB. The noise floor of the system is −89.9 dBm. Compared to only using aperture optimization and only using beamforming technology, the scheme in this paper, respectively, improves the isolation of 20.69 and 6.17 dB.

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