On the Impossibility of Lossless Waveform Rank Reduction for Certain Redundant Arrays

Efficient use of spatio-temporal resources, including sensor arrays and transmit waveforms, is a key challenge in modern MIMO active sensing systems. This paper studies the impact of array redundancy and WR on active sensing performance. Specifically, we show that parameter identifiability atreducedWR critically depends on subspace properties of the so-called array redundancy pattern. We show that array geometries with identical sum co-arrays can exhibit markedly different identifiability properties at low WR. We derive a novel necessary condition for maximizing identifiability at reduced WR, which reveals that the unfavorable redundancy patterns of certain redundant arrays fundamentally limits their performance. The results yield new insights into resource-efficient sensing systems, motivating redundancy-aware array and waveform design.