Stochastic optimization methods applied to microwave imaging: A review

Stochastic methods are now very common in electromagnetics. Among the various applications, they have been recently proposed for solving inverse problems arising in radio-frequency and microwave imaging. Some of the recently proposed stochastic inversion procedures are critically discussed (e.g., genetic algorithms, differential evolution methods, memetic algorithms, particle swarm optimizations, hybrid techniques, etc.) and the way they have been applied in this area. The use of the ant colony optimization method, which is a relatively new method in electromagnetics, is also proposed. Various imaging modalities are considered (tomography, buried object detection, and borehole sensing). Finally, the main features making these approaches useful for imaging purposes are discussed and the currently considered strategies to reduce the computational load associated with stochastic optimization procedures delineated.