Non Co-Operative Detection of LPI/LPD Signals Via Cyclic Spectral Analysis.

Abstract

This research proposes and evaluates a novel technique for detecting LPI/LPD communication signals using a digital receiver primarily designed to detect radar signals, such as a Radar Warning Receiver (RWR) or an Electronic Support Measures (ESM) receiver. The proposed Cyclic Spectrum Analysis (CSA) receiver is a robust detector that takes advantage of the spectral correlation properties of second-order cyclostationary signals. A computationally efficient algorithm is used to estimate the Spectral Correlation Function (SCF). Using state-of-the-art FFT processing, it is expected that the proposed CSA receiver architecture could estimate the entire cyclic spectrum m approximately 0.6 ms. The estimate is then reduced to an energy related test statistic that is valid for all cycle frequencies within the receiver bandwidth. By producing an estimate of the cyclic spectrum, the CSA receiver also benefits post-detection tasks such as signal classification and exploitation. As modeled, the ideal CSA receiver detection performance is within 1.0 dB of the radiometer in benign signal environments and consistently outperforms the radiometer in adverse signal environments. The effect on detection performance when the CSA receiver is implemented with channelized and quadrature digital receiver architectures is also examined.

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Document Details

Document Type
Technical Report
Publication Date
Mar 01, 1999
Accession Number
ADA361720

Entities

People

  • Andrew M. Gillman

Organizations

  • Air Force Institute of Technology

Tags

Communities of Interest

  • Air Platforms
  • Energy and Power Technologies
  • Materials and Manufacturing Processes

DTIC Thesaurus Topics

  • Algorithms
  • Amplitude Modulation
  • Bandwidth
  • Communication Systems
  • Computational Science
  • Detection
  • Detectors
  • Digital Signal Processing
  • Electrical Engineering
  • Electronic Warfare
  • Frequency Bands
  • Probabilistic Models
  • Random Variables
  • Spectrum Analysis
  • Stationary Processes
  • Stochastic Processes
  • Warning Systems

Fields of Study

  • Engineering

Readers

  • Radar Systems Engineering.
  • Radio communications and signal processing.

Technology Areas

  • Microelectronics