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Optimisation in Signal and Image Processing by Patrick Siarry

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Chapter 7

Optimizing Emissions for Tracking and Pursuit of Mobile Targets

7.1. Introduction

Increasingly intricate problems and a variety of available sensors based on quite different physical principles have led to the increasing necessity of optimizing the usage of resources. It is assumed here that the sensors are collocated but differ in their essential characteristics such as the type of observations, detection performance, geographical coverage and the cost of usage. This chapter only deals with tracking problems.

The problems addressed here are rather simply formalized. The system has passive as well as active measurements. Passive measurements do not include the estimation of the target’s complete state and typically are limited to the estimation of the target’s direction (if partially observed). Passive measurements thus imply (1D) non-linear functions with a noisy state. On the other hand, the system is able to emit (active measurements). These measurements provide a direct estimation of the distance to the target, but generate cost. This cost is limited by a global budget. The global budget covers different factors such as the surveillance capacity of the entire system, risks, etc. Several practical examples could illustrate this type of problem. For example, an aeroplane used for maritime patrol has active and passive sensors in order to accomplish its mission. Passive sensors are, for example, electronic support measurements (ESM) and an active sensor is, for example, ...

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