Smoothing is a better tool for denoising at some past data point. Since the computational complexity of smoothing algorithms is usually not an issue in practice, their usefulness is appreciated in many areas of signal processing. This chapter discusses optimal finite impulse response (OFIR) smoothing techniques and problems by looking at and using various combinations of forward and backward models and filtering schemes. A simple and quite straightforward smoothing technique is fixed‐interval two‐filter smoothing . Smoothing solutions can be found mainly in post‐processing algorithms, although some real‐time estimators also incorporate smoothing procedures where the lag q does not introduce significant bias errors. Finite impulse response smoothing algorithms that operate with full block noise and error matrices are preferable in terms of accuracy over recursive schemes that are available when such matrices are diagonal.
Optimal FIR Smoothing
Optimal and Robust State Estimation ; 159-187
2022-08-09
29 pages
Article/Chapter (Book)
Electronic Resource
English
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