Detection Based on Multiple Observations: Nonfluctuating Model

Detection Based on Multiple Observations: Nonfluctuating Model

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In Chapter 9 we investigated the structure and performance of an optimum receiver on the basis of a single observation. In this chapter we examine the optimum Bayes receiver structure and performance when many observations are available for detection. The radar waveform transmitted is assumed to be identical within each observation interval; a sequence of waveform echoes from a target is called a pulse train.

Chapter Contents:

  • 10.1 Introduction
  • 10.2 Nonfluctuating Coherent Pulse Train
  • 10.3 Optimum Receiver Structure for a Nonfluctuating Incoherent Pulse Train
  • 10.4 Small-Signal Optimum Receiver Performance
  • 10.5 Integration Loss for Nonfluctuating Incoherent Detector
  • 10.6 Gram-Charlier Series
  • 10.7 Analytic Approximations (Nonfluctuating Incoherent Detector)
  • 10.8 Linear versus Square-Law Detection
  • Problems
  • References

Inspec keywords: Bayes methods; radar detection

Other keywords: waveform echo sequence; nonfluctuating model; pulse train; radar waveform transmission; observation interval; multiple-observation detection

Subjects: Signal detection; Other topics in statistics; Radar theory

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