Digital filters (Mathematics)

The design of high order switched-capacitor highpass filters is
presented. Emphasis is placed on the design procedures of cascaded
biquadratic sections and ladder network realizations of switchedcapacitor
highpass filters. The stability problem of the doubly terminated
switched-capacitor ladder highpass filter is discussed. Design
examples are presented to illustrate the design procedures. The
sensitivities of the realization methods are discussed. An .analytical
equation of the gain deviation for the cascaded biquadratic sections
realization is derived. Monte Carlo analysis is performed for the
design examples. The results of the analyses are compared to reveal
the differences in sensitivities in terms of the order of the filters
and the type of realizations.

In this dissertation, identification and approximation of one-dimensional (1-D) and two-dimensional (2-D) recursive digital filters are addressed. In the identification phase, a novel Neural Network (NN) structure is proposed which provides the state-space model of 1-D filters based upon input-output data. The state space identification technique is also extended to 2-D digital filters and several comparison studies are performed. In the approximation phase, frequency-domain balanced structures for 1-D as well as 2-D digital filters are proposed. The model reduction technique is based on the conceptual view point of balancing the controllability and observability Grammians of a digital filter in an arbitrary frequency range of operation. Finally, the interrelations between these two phases are presented. Extensive simulation experiments are presented to demonstrate the effectiveness of proposed methods.

This thesis proposes to estimate the speed of a moving acoustic source by either linear or non linear processing of the resulting Doppler shift present in a high-frequency pilot tone. The source is an acoustic modem (Hermes) which currently uses moving average to estimate and compensate for Doppler shift. A new auto regressive approach to Doppler estimation (labeled IIR method in the text) promises to give a better estimate. The results for a simulated peak velocity of 2 m/s in the presence of additive noise showed an RMSE of 0.23 m/s using moving average vs. 0.00018 m/s for the auto regressive approach. The SNR was 75 dB. The next objective was to compare the estimated Doppler velocity obtained using the two algorithms with the experimental values recorded in real time. The setup consisted of a receiver hydrophone attached to a towing carriage that moved with a known velocity with respect to a stationary acoustic source. The source transmitted 375 kHz pilot tone. The received pilot tone data were preprocessed using the two algorithms to estimate both Doppler shift and Doppler velocity. The accuracy of the algorithms was compared against the true velocity values of the carriage. The RMSE for a message from experiments conducted indoor for constant velocity of 0.4 m/s was 0.6055 m/s using moving average, 0.0780 m/s using auto regressive approach. The SNIR was 6.3 dB.