Sparse Array Optimization by Using the Simulated Annealing Algorithm

Sparse synthetic transmit aperture (STA) imaging systems are a good alternative to the conventional phased array systems. Unfortunately, the sparse STA imaging systems suffer from some limitations, which can be overcome with a proper design. In order to do so, a simulated annealing algorithm, combined with an effective approach can used for optimization of a sparse STA ultrasound imaging system. In this paper, three two-stage algorithms for optimization of both the positions of the transmit sub-apertures and the weights of the receive elements are considered and studied. The first stage of the optimization employs a simulated annealing algorithm that optimizes the locations of the transmit sub-aperture centers for a set of weighting functions. Three optimization criteria used at this stage of optimization are studied and compared. The first two criteria are conventional. The third criterion, proposed in this paper, combines the first two criteria. At the second stage of optimization, an appropriate weighting function for the receive elements is selected.

The sparse STA system under study employs a 64-element array, where all elements are used in receive and six sub-apertures are used in transmit. Compared to a conventional phased array imaging system, this system acquires images of better quality 21 times faster than an equivalent phased array system.