KEYWORDS: Filtering (signal processing), Electronic filtering, Signal processing, Smoothing, Interference (communication), Control systems, Digital signal processing, Electromagnetic coupling, Data processing, Nonlinear filtering
Moving average filters are commonly used in industries for real-time processing of noisy data. Though they perform well in filtering out the noise, they introduce significant lag in the signal. The resulting peak value of the filtered signal at the operating point is likely to be lower due to averaging of higher and lower peak signals in the averaging interval. The generalized moving average smoothing filter by Golay-Savitzky preserves the higher moments and does not suffer from the limitations imposed by the conventional moving average filter. The smoothing strategy is derived from least squares fitting of a lower order polynomial to a number of consecutive points. Due to polynomial curve fitting as opposed to a line fitting in the case of conventional moving average filter, this filter preserves the higher frequency components of the signal and their line width. This paper presents a generalized casual moving average filter deduced using the concepts in Golay-Savitzky smoothing filter for real-time applications. Golay-Savitzky filter is non-casual, relies on the future data that is not available, hence not suitable for real-time applications. Further, the designed casual filter makes use of the filtered data as opposed to the original data in the case of Golay-Savitzky. This approach allows us to conduct frequency response studies to evaluate the quality and the applicability of the filter for various signals in the aircraft engines and other engineering applications. Frequency response studies cannot carried out using the Golay-Savitzky filter. This paper also investigates the performance of various polynomial orders in reproducing the signal from a noisy data. Some of the performance measures used are bandwidth, overshoots, and lags introduced by the filter. The mathematical technique to extract the signal and deduce the coefficients in off-line is also presented.
This paper presents the design and implementation of a high performance vehicle controller based on parallel digital processing systems for automated vehicles. From the literature it has been observed that one of the main limiting factors of most automated vehicles rests on the available computing power. Most systems employ camera vision for guidance purposes. In some cases other sensors are used in combination with camera vision. The amount of information that has to be processed can overwhelm many processors. Solutions so far involved distributed processing, massively parallel processors, dedicated processors and mini computers. In most cases, these systems use specially designed processors, lacking standard interfacing, and as a result proprietary interface cards have to be built. This paper takes the alternate approach of designing a high performance controller using the parallel DSP systems, namely, the TMS320C40 processors with 275 MIPS and 50 MFLOPS. This controller processes data from a CCD camera which is focused onto a road segment containing a line that has suitable contrast with the road surface. The DSP based controller in a PC environment. Carries out the task of high level control while the low level servo control is assigned to dedicated motion controllers communicating with the DSP based controller through the PC bus. Results of image processing and timing requirements for various topologies are detailed.
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