Detection of Multiple R/C Devices using MVDR and Genetic Algorithms


Reflections, multipath propagation, and scattering creates phantom sources of signal. In addition, reliable detection of radio controlled (RC) devices in the presence of multiple actual devices is a challenging task. RC devices employing super regenerative receivers (SRRs) and super heterodyne receivers emit unintended radiations in their ON-state. This paper introduces a novel detection scheme that combines self-similarity and received signal strength indicator (RSSI)-based detection with minimum variance distortionless response (MVDR) method. In addition, detection accuracy is improved using multiconstrained genetic algorithms (GAs). RSSI method detects multiple devices from received signal strength and Hurst parameter identifies self-similar SRR devices. Regularized MVDR improves detection of multiple devices by jamming unwanted signals and signals from known angle of arrival. Regularization reduces variation in detection due to environmental noise. Multiconstrained GA is implemented in the cases where MVDR fails. The experimental results for detection have also been presented for multiple SRR receivers (door bells at 315 MHz).


Electrical and Computer Engineering

Keywords and Phrases

Algorithms; Direction of arrival; Genetic algorithms; Heterodyning; Radio receivers; Signal receivers; Detection accuracy; Environmental noise; Genetic algorithm (GAs); Minimum variance distortionless response; Received signal strength; Received signal strength indicators; Super-regenerative receiver; Superheterodyne receivers; Signal detection; Array detectors; Detection; Hurst parameter; Minimum variance distortionless response (MVDR); Received signal strength indicator (RSSI); Super regenerative receiver (SRR); Unintended emissions (UEs)

International Standard Serial Number (ISSN)

0018-9456; 1557-9662

Document Type

Article - Journal

Document Version


File Type





© 2015 Institute of Electrical and Electronics Engineers (IEEE), All rights reserved.

Publication Date

01 Oct 2015