Modulation Recognition Algorithms for Intentional Modulation on Pulse (IMOP) applications

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Authors
  1. Sung, S.
  2. Zhou, Y.
Corporate Authors
Defence Research Establishment Ottawa, Ottawa ONT (CAN)
Abstract
In this report, the problem of signal modulation classification is investigated. A modulation recognition algorithm for classifying different signal modulation types and noise is described. The modulation type includes unmodulated CW, narrow-band FM, wide-band FM, triangular FM, BPSK, DSB-SC and AM. The algorithym involves a combination of decision theoretic and pattern recognition techniques. The decision theoretic technique is based on the calculation of a number of statistics of the input sequence to be classified. It is used to separate noise from the signals, the constant-envelope waveforms with phase information, and the two varying-envelope waveforms from one another. The pattern recognition technique is used to distinguish the three FM and BPSK waveforms. The technique is based on the use of a linear discriminant. The discriminant is trained by feature vectors generated from the residual-phase histogram. Finally, computer simulations are used to demonstrate the performance of the proposed modulation recognition algorithm, and an extensive analysis is also included.

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Keywords
IMOP (Intentional Modulation On Pulse);Target identification;Pulse trains;Modulation recognition;Decision theoretic;Linear discriminant
Report Number
DREO-TR-2001-111 — Technical Report
Date of publication
01 Dec 2001
Number of Pages
56
DSTKIM No
CA020899
CANDIS No
517628
Format(s):
Hardcopy;Document Image stored on Optical Disk

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