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Low-Complexity Addition or Removal of Sensors/Constraints in LCMV Beamformers

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3 Author(s)
Shmulik Markovich-Golan ; Bar-Ilan University, School of Engineering, Ramat-Gan, Israel ; Sharon Gannot ; Israel Cohen

We address the application of the linearly constrained minimum variance (LCMV) beamformer in sensor networks. In signal processing applications, it is common to have a redundancy in the number of nodes, fully covering the area of interest. Here we consider suboptimal LCMV beamformers utilizing only a subset of the available sensors for signal enhancement applications. Multiple desired and interfering sources scenarios in multipath environments are considered. We assume that an oracle entity determines the group of sensors participating in the spatial filtering, denoted as the active sensors. The oracle is also responsible for updating the constraints set according to either sensors or sources activity or dynamics. Any update of the active sensors or of the constraints set necessitates recalculation of the beamformer and increases the power consumption. As power consumption is a most valuable resource in sensor networks, it is important to derive efficient update schemes. In this paper, we derive procedures for adding or removing either an active sensor or a constraint from an existing LCMV beamformer. Closed-form, as well as generalized sidelobe canceller (GSC)-form implementations, are derived. These procedures use the previous beamformer to save calculations in the updating process. We analyze the computational burden of the proposed procedures and show that it is much lower than the computational burden of the straightforward calculation of their corresponding beamformers.

Published in:

IEEE Transactions on Signal Processing  (Volume:60 ,  Issue: 3 )