Over a Century of Array Signal Processing
Since the introduction of phased array in 1905 by Karl Braun, a Nobel Laureate, array signal processing has advanced significantly over the past century. The era of adaptive array was started by Jack Capon, signified by his seminal paper in 1969. The Capon beamformer has better resolution and much better interference rejection capability than the data-independent beamformer by Karl Braun, provided that the array steering vector corresponding to the signal of interest (SOI) and the array covariance matrix is accurately known, and the SOI is uncorrelated to all other signals impinging on the array. However, whenever the knowledge of the SOI steering vector is imprecise, the number of data snapshots is scarce, or the SOI is correlated with a multipath, which are often the cases encountered in practice, the performance of the Capon beamformer may become worse than that of the data-independent beamformer. For over 50 years, making the Capon beamformer robust has attracted much interest and tens of thousands of papers on robust adaptive array processing have been published in the literature. To fundamentally overcome the limitations of the Capon family of beamformers, iterative approaches have been introduced in the recent literature. Most notably, the iterative adaptive approach (IAA) was published in 2010 and is shown to possess strong robustness, and can work well under single snapshot and arbitrary array scenarios. We will compare the non-parametric and user parameter free IAA algorithm with other well-known algorithms, including the data-independent beamformer, the Capon beamformer, the OMP algorithm introduced in the compressed sensing literature, as well as the parametric MUSIC and ESPRIT algorithms.