The Cramér–Rao Bound for Signal Parameter Estimation From Quantized Data [Lecture Notes]

Abstract

Several current ultrawide band applications, such as millimeter-wave radar and communication systems <xref ref-type="bibr" rid="ref1" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[1]</xref> – <xref ref-type="bibr" rid="ref2" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"/> <xref ref-type="bibr" rid="ref3" xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">[3]</xref> , require high sampling rates and therefore expensive and energy-hungry analog-to-digital converters (ADCs). In applications where cost and power constraints exist, the use of high-precision ADCs is not feasible, and the designer must resort to ADCs with coarse quantization. Consequently, the interest in the topic of signal parameter estimation from quantized data has increased significantly in recent years.