Error spectrum shaping quantization
Error spectrum shaping (ESS) quantizers reduce quantization error in bandlimited signals by reducing quantizer error power in the signal band at the expense of increased error power outside the signal band. The error power outside the signal band is subsequently reduced by a reconstruction filter. The original analysis of ESS quantizers was based on ideal reconstruction filters and did not consider the effects of realizable reconstruction filters. Nor did the original analysis consider the effects of quantizer saturation or stability. Consequently, predictions of ESS quantizer distortion were often optimistic. This dissertation reports the extension of the original analysis to account for realistic reconstruction filters, saturation, and stability. Simulations show that the extended analysis accurately predicts the distortion of realistic ESS quantizers. ESS quantization is then applied to interferometric data using the extended analysis. A gain in signal-to-noise ratio of up to 30 dB over memoryless quantization was achieved for the interferometric data, using the same reconstruction filter and bit rate in both cases.