One method to account for parameters errors in the Kalman filter is to consider their effect in the so-called Schmidt-Kalman filter. This work addresses issues that arise when implementing a consider Kalman filter as a real-time, recursive algorithm. A favorite implementation of the Kalman filter as an onboard navigation subsystem is the UDU formulation. A new way to implement a UDU consider fi...

One method to account for parameters errors in the Kalman filter is to ‘consider’ their effect in the so-called Schmidt-Kalman filter. This paper addresses issues that arise when implementing a consider Kalman filter as a real-time, recursive algorithm. A favorite implementation of the Kalman filter as an onboard navigation subsystem is the UDU formulation. A new way to implement a UDU Schmidt-...

Exponentially weighted recursive least-squares (RLS) algorithms are commonly used for fast adaptation. In many cases the input signals are continuous-time. Either a fully analog implementation of the RLS algorithm is applied or the input data are sampled by analog-to-digital (AD) converters to be processed digitally. Although a digital realization is usually the preferred choice, it becomes unf...

In the cascade realization of fixed-point digital filters underdynamic range constraints, the output noise due to accumulation ofroundoff errors is highly dependent upon the order of the sections.For recursive filters it also depends on the pole—zero pairing that formsthe individual second-order sections. The output noise may vary overseveral orders of magnitude for differen...

Combining the methods of generating functions and discrete-time linear systems, we can develop multidimensional (M-D) digital systems for systematic generation of entire families of interrelated digital filters. These M-D systems, dubbed filter-generating systems, are mostly of infinite-impulse response (IIR) type and can produce the impulse response sequence of any member of the family. Tempor...

We propose a new strategy to design recursive implementations of the Gaussian filter and Gaussian regularized derivative filters. Each recursive filter consists of a cascade of two stable Nth-order subsystems (causal and anti-causal). The computational complexity is 2N multiplications per pixel per dimension independent of the size (σ) of the Gaussian kernel. The filter coefficients have a clos...

There have been many 2D (two–dimensional) VLSI structures introduced in the literature for 1D (one–dimensional) recursive digital filters with high throughput. The technique applied for the implementations is mainly based on block–state–variable filter descriptions. This paper introduces a high throughput systolic implementation of direct form second order recursive filters. The systolic struct...

The aim of this paper is to construct non-recursive filters, extensively used type digital filters in signal processing applications, based on Chebyshev orthogonal polynomials. proposes the use fourth-kind polynomials as functions generating new filters. In kind, low-pass with linear phase responses are obtained. Comprenhansive study frequency response characteristics generated filter presented...