Sensor Selection for Angle of Arrival Estimation Based on the Two-Target Cramér-Rao Bound

Sensor selection is a useful method to help reduce data throughput, as well as computational, power, and hardware requirements, while still maintaining acceptable performance. Although minimizing the Cramér-Rao bound has been adopted previously for sparse sensing, it did not consider multiple targets and unknown source models. In this work, we...

Single-Pulse Estimation of Target Velocity on Planar Arrays

Doppler velocity estimation in pulse-Doppler radar is done by evaluating the target returns of bursts of pulses. While this provides convenience and accuracy, it requires multiple pulses. In adaptive and cognitive radar systems, the ability to adapt on consecutive pulses, instead of bursts, brings potential performance benefits. Hence, with...

Uniaxial Acoustic Vector Sensors for direction-of-arrival estimation

In this paper, a specific reduced-channel Acoustic Vector Sensor (AVS) is proposed comprising one omni-directional microphone and only one particle velocity transducer, such that it can have an arbitrary orientation. Such a reduced transducer configuration is referred to as a Uniaxial AVS (U-AVS). The DOA performance of an array of U-AVSs is...

Functional Cramér–Rao bounds and Stein estimators in Sobolev spaces, for Brownian motion and Cox processes

We investigate the problems of drift estimation for a shifted Brownian motion and intensity estimation for a Cox process on a finite interval [0,T], when the risk is given by the energy functional associated to some fractional Sobolev space . In both situations, Cramér–Rao lower bounds are obtained, entailing in particular that no unbiased...

Complex Factor Analysis

Many techniques for array processing assume either that the system has a calibrated array or that the noise covariance matrix is known. If the noise covariance matrix is unknown, training or other calibration techniques are used to find it. In this thesis another approach to the problem of unknown noise covariance is presented. The factor...

Ranging energy optimization for robust sensor positioning based on semidefinite programming

Sensor positioning is an important task of location-aware wireless sensor networks. In most sensor positioning systems, sensors and beacons need to emit ranging signals to each other. Sensor ranging energy should be low to prolong system lifetime, but sufficiently high to fulfill prescribed accuracy requirements. This motivates us to investigate...

Performance of optimal registration estimators

This paper derives a theoretical limit for image registration and presents an iterative estimator that achieves the limit. The variance of any parametric registration is bounded by the Cramer-Rao bound (CRB). This bound is signal-dependent and is proportional to the variance of input noise. Since most available registration techniques are biased...