Jointly Optimal Array Geometries and Waveforms in Active Sensing

New Insights Into Array Design via the Cramér-Rao Bound

Journal Article (2025)
Author(s)

I. van der Werf (TU Delft - Signal Processing Systems)

G. Leus (TU Delft - Signal Processing Systems)

Robin Rajamäki (Aalto University)

Research Group
Signal Processing Systems
DOI related publication
https://doi.org/10.1109/ICASSP49660.2025.10890202
More Info
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Publication Year
2025
Language
English
Research Group
Signal Processing Systems
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository as part of the Taverne amendment. More information about this copyright law amendment can be found at https://www.openaccess.nl. Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public. @en
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Abstract

This paper investigates jointly optimal array geometry and waveform designs for active sensing. Specifically, we focus on minimizing the Cramér-Rao lower bound (CRB) of the angle of a single target in white Gaussian noise. We first find that several array-waveform pairs can yield the same CRB by virtue of sequences with equal sums of squares, i.e., solutions to certain Diophantine equations. Furthermore, we show that under physical aperture and sensor number constraints, the CRB-minimizing receive array geometry is unique, whereas the transmit array can be chosen flexibly. We leverage this freedom to design a novel sparse array geometry that not only minimizes the single-target CRB given an optimal waveform, but also has a nonredundant and contiguous sum co-array—a desirable property when launching independent waveforms, with relevance also to the multi-target case.

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