Suboptimal robust sinusoidal frequency estimation

It has been shown that an L_p normed solution to linear prediction equations may be advantageous in certain time-series modeling applications. Specifically, in the context of sinusoidal frequency estimation from data contaminated by impulsive noise, choosing p=1 may result in less biased frequency estimates. Computing L_p normed solutions requires iterative methods that are computationally expensive. By plotting prediction error filter root migration in the complex z-plane as a function of iteration step one is able to construct a suboptimal weighted least-squares solution. This solution, though not an L _p normed solution, is still robust against impulsive noise and is not as computationally expensive as iterating to a true L_p normed solution