A survey of the state of the art and focused research in range systems, task 2

Contract generated publications are compiled which describe the research activities for the reporting period. Study topics include: equivalent configurations of systolic arrays; least squares estimation algorithms with systolic array architectures; modeling and equilization of nonlinear bandlimited satellite channels; and least squares estimation and Kalman filtering by systolic arrays

Frequency sampling digital filters for multirate applications and pipelined implementations

Under certain circumstances, narrowband linear phase filters can be implemented more efficiently using frequency sampling filters than direct convolution filters. The desired frequency response of a frequency sampling filter is approximated by interpolating a frequency response through a set of frequency samples. The implementation of a frequency sampling filter contains unit delays in its feedback paths. Therefore, it cannot be pipelined or efficiently used in multirate applications. In this thesis, a frequency sampling filter that has only delays of length D in it feedback paths is developed. The new frequency sampling filter can be pipelined and efficiently used in multirate applications

Design of a reusable distributed arithmetic filter and its application to the affine projection algorithm

Digital signal processing (DSP) is widely used in many applications spanning the spectrum from audio processing to image and video processing to radar and sonar processing. At the core of digital signal processing applications is the digital filter which are implemented in two ways, using either finite impulse response (FIR) filters or infinite impulse response (IIR) filters. The primary difference between FIR and IIR is that for FIR filters, the output is dependent only on the inputs, while for IIR filters the output is dependent on the inputs and the previous outputs. FIR filters also do not sur from stability issues stemming from the feedback of the output to the input that aect IIR filters. In this thesis, an architecture for FIR filtering based on distributed arithmetic is presented. The proposed architecture has the ability to implement large FIR filters using minimal hardware and at the same time is able to complete the FIR filtering operation in minimal amount of time and delay when compared to typical FIR filter implementations. The proposed architecture is then used to implement the fast affine projection adaptive algorithm, an algorithm that is typically used with large filter sizes. The fast affine projection algorithm has a high computational burden that limits the throughput, which in turn restricts the number of applications. However, using the proposed FIR filtering architecture, the limitations on throughput are removed. The implementation of the fast affine projection adaptive algorithm using distributed arithmetic is unique to this thesis. The constructed adaptive filter shares all the benefits of the proposed FIR filter: low hardware requirements, high speed, and minimal delay.Ph.D.Committee Chair: Anderson, Dr. David V.; Committee Member: Hasler, Dr. Paul E.; Committee Member: Mooney, Dr. Vincent J.; Committee Member: Taylor, Dr. David G.; Committee Member: Vuduc, Dr. Richar

High-speed digital filtering: Structures and finite wordlength effects

This paper is a study of high-throughput filter structures such as block structures and their behavior in finite precision environments. Block structures achieve high throughput rates by using a large number of processors working in parallel. It has been believed that block structures which are relatively robust to round-off noise must also be robust to coefficient quantization errors. However, our research has shown that block structures, in fact, have high coefficient sensitivity. A potential problem that arises as a result of coefficient quantization is a periodically time-varying behavior exhibited by the realized filter. We will demonstrate how finite wordlength errors can change a nominally time-invariant filter into a time-varying system. We will identify the block structures that have low coefficient sensitivity, and develop high-speed structures that are immune to the time-varying problems caused by coefficient quantization.Peer Reviewedhttp://deepblue.lib.umich.edu/bitstream/2027.42/41355/1/11265_2004_Article_BF00930646.pd

An Architecture for On board Frequency Domain Analysis of Launch Vehicle Vibration Signals

The dynamic properties of the airborne structures plays a crucial role in the stability of the vehicle during flight. Modal and spectral behaviour of the structures are simulated and analysed. Ground tests are carried out with environmental conditions close to the flight conditions, with some assumptions. Subsequently, based on the flight telemetered data, the on-board mission algorithm and the auto-pilot filter coefficients are fine tuned. An attempt is made in this paper to design a novel architecture for analysing the modal and spectral random vibration signals on-board the flight vehicle and to identify the dominant frequencies. Based on the analysed results, the mission mode algorithm and the filter coefficients can be fine tuned on-board for better effectiveness in control and providing more stability. Three types of windows viz. Hann, Hamming and Blackman-Harris are configured with a generalised equation using FIR filter structure. The overlapping of the input signal data for better inclusiveness of the real-time data is implemented with BRAM. The domain conversion of the data from time domain to frequency domain is carried out with FFT using Radix-2 BF architecture. The FFT output data are processed for calculating the power spectral density. The dominant frequency is identified using the array search method and Goldschmidt algorithm is utilised for the averaging of the PSDs for better precision. The proposed architecture is synthesised, implemented and tested with both Synthetic and doppler signal of 300 Hz spot frequency padded with Gaussian white noise. The results are highly satisfactory in identifying the spot frequency and generating the PSD array

Hardward and algorithm architectures for real-time additive synthesis

Additive synthesis is a fundamental computer music synthesis paradigm tracing its origins to the work of Fourier and Helmholtz. Rudimentary implementation linearly combines harmonic sinusoids (or partials) to generate tones whose perceived timbral characteristics are a strong function of the partial amplitude spectrum. Having evolved over time, additive synthesis describes a collection of algorithms each characterised by the time-varying linear combination of basis components to generate temporal evolution of timbre. Basis components include exactly harmonic partials, inharmonic partials with time-varying frequency or non-sinusoidal waveforms each with distinct spectral characteristics. Additive synthesis of polyphonic musical instrument tones requires a large number of independently controlled partials incurring a large computational overhead whose investigation and reduction is a key motivator for this work. The thesis begins with a review of prevalent synthesis techniques setting additive synthesis in context and introducing the spectrum modelling paradigm which provides baseline spectral data to the additive synthesis process obtained from the analysis of natural sounds. We proceed to investigate recursive and phase accumulating digital sinusoidal oscillator algorithms, defining specific metrics to quantify relative performance. The concepts of phase accumulation, table lookup phase-amplitude mapping and interpolated fractional addressing are introduced and developed and shown to underpin an additive synthesis subclass - wavetable lookup synthesis (WLS). WLS performance is simulated against specific metrics and parameter conditions peculiar to computer music requirements. We conclude by presenting processing architectures which accelerate computational throughput of specific WLS operations and the sinusoidal additive synthesis model. In particular, we introduce and investigate the concept of phase domain processing and present several “pipeline friendly” arithmetic architectures using this technique which implement the additive synthesis of sinusoidal partials