Passive MIMO radar networks

Passive MIMO radar networks

For access to this article, please select a purchase option:

Buy chapter PDF
(plus tax if applicable)
Buy Knowledge Pack
10 chapters for $120.00
(plus taxes if applicable)

IET members benefit from discounts to all IET publications and free access to E&T Magazine. If you are an IET member, log in to your account and the discounts will automatically be applied.

Learn more about IET membership 

Recommend Title Publication to library

You must fill out fields marked with: *

Librarian details
Your details
Why are you recommending this title?
Select reason:
Novel Radar Techniques and Applications Volume 1: Real Aperture Array Radar, Imaging Radar, and Passive and Multistatic Radar — Recommend this title to your library

Thank you

Your recommendation has been sent to your librarian.

In distributed sensing applications, the nodes of a sensor network cooperatively detect and localize targets of interest. In particular, active multiple-input multipleoutput (MIMO) radar (AMR) uses multiple transceivers to transmit separable signals and receive the scattered returns, while passive MIMO radar (PMR) uses multiple receivers to receive the direct-path (transmitter-to-receiver) and target-path (transmitter-to-target-to-receiver) signals originated by multiple non-cooperative transmitters to detect and localize targets. This chapter surveys recent results in the theory of centralized detection in PMR networks. Generalized likelihood ratio test (GLRT)-based detectors for PMR detection have been developed and their performances are compared to related detectors for AMR and passive source localization (PSL) sensor networks. PMR detection sensitivity and ambiguity are then analyzed as a function of both the target-path and direct-path signals-to-noise ratios (SNRs). The results demonstrate that PMR detection sensitivity and ambiguity approach that of active MIMO radar sensor networks when the direct-path SNRs are sufficiently high. Conversely, PMR detection sensitivity and ambiguity approximate that of passive source localization sensor networks when the direct-path SNRs are sufficiently low. In this way, PMR networks unify these related active and passive sensor network architectures in a common theoretical framework.

Chapter Contents:

  • Abstract
  • 19.1 Introduction
  • 19.2 Signal models
  • 19.2.1 Passive MIMO radar
  • 19.2.2 Active MIMO radar
  • 19.2.3 Passive source localization
  • 19.3 Centralized GLRT detection
  • 19.3.1 Passive MIMO radar
  • Relationship to cross-ambiguity function processing
  • 19.3.2 Active MIMO radar
  • 19.3.3 Passive source localization
  • 19.3.4 Detector comparisons
  • 19.3.5 Probability distributions
  • 19.4 Detection sensitivity
  • 19.4.1 Simulation scenario
  • 19.4.2 Dependence on reference and surveillance SNR
  • 19.4.3 Dependence on signal length
  • 19.4.4 Discussion
  • 19.5 Detection ambiguity
  • 19.5.1 Dependence on waveform ambiguity
  • 19.5.2 Simulation scenario
  • 19.5.3 AMR ambiguity
  • 19.5.4 PSL ambiguity
  • 19.5.5 PMR ambiguity
  • 19.6 Conclusion
  • References

Inspec keywords: radar receivers; object detection; radar detection; radar transmitters; passive radar; MIMO radar

Other keywords: signals-to-noise ratio; GLRT-based detectors; SNR; passive MIMO radar network; PMR detection sensitivity approach; active multiple input multiple output radar; generalized likelihood ratio test-based detectors; AMR; direct-path signals; multiple transceivers; multiple receivers; target localization; target-path signals; multiple noncooperative transmitter; distributed sensing applications; PMR detection ambiguity approach; sensor network node; target detection; PMR networks

Subjects: Signal detection; Radar equipment, systems and applications

Preview this chapter:
Zoom in

Passive MIMO radar networks, Page 1 of 2

| /docserver/preview/fulltext/books/ra/sbra512f/SBRA512F_ch19-1.gif /docserver/preview/fulltext/books/ra/sbra512f/SBRA512F_ch19-2.gif

Related content

This is a required field
Please enter a valid email address