Fixed‐Memory Polynomial Filter
Eli Brookner DSc · 1998
The fixed-memory polynomial filter is covered in Chapter 5. In Section 5.3 the DOLP approach is applied to the tracking and least-squares problem for the important cases where the target trajectory or data points (of which there are a fixed number L+1) are approximated by a polynomial fit of some degree m. The convenient and useful representation of the polynomial fit of degree m in terms of the target equation motion derivatives (first m derivatives) is given in Section 5.4. A useful general solution to the DOLP least-squares estimate for a polynomial fit that is easily solved on a computer is given in Section 5.5. Sections 5.6 through 5.10 present the variance and bias errors for the least-squares solution and discuss how to balance these errors. The important method of trend removal to lower the variance and bias errors is discussed in Section 5.11.