Properties of Hung-Turner projections and their relationship to the eigencanceller

Hung-Turner (1983) projections have been proposed as a computationally efficient method of computing adaptive array weights. An exact relationship between Hung-Turner projections and the eigencanceller is noted, and used to analyze their performance. A simple and intuitive derivation is given for the expected SINR loss of Hung-Turner projections. This leads to a formula for the optimal number of snapshots (training samples). An expression for the expected sidelobe levels of weights computed using Hung-Turner projections is also derived.