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Session B1: Receiver Signal Processing

Doppler Considerations and Phase Manifold Effects for Anti-jam Electronics
Adam Simmons, Greg Reynolds, Russell Powell, Caleb Perry, Laura Mcrain, Brian Baeder and Timothy Pitt, Army AMRDEC
Location: Cypress

Due to the widespread use of anti-jam electronics (AJ-E) and controllable radiation pattern antennas (CRPA), considerations of Doppler effects and its contributions through an antennas phase manifold need to be considered. Most AJ-E units use an estimated covariance matrix to derive weights for their individual antenna element feeds and taps. This estimated covariance matrix is typically estimated by a windowed set of Inphase and Quadrature phase (IQ) samples collected over 1 ms of time. Most per-element delays are constant over this 1 ms period, but some vehicles hosting the AJ-E have benign roll rates which when mapped through the antenna phase manifold can create Doppler coloring of the covariance estimate. This paper examines the Doppler influence through a commercial CRPA's phase manifold and maps the per-component phase error perceived. The paper demonstrates the effect through software simulated IQ data samples, a commercial phase manifold and via hardware-in-loop wavefront simulation.
First, this paper provides the reader an intuitive approach to understanding the relationship between vehicle roll-rate, phase manifold gradients and the resulting Doppler effects. This understanding is illustrated through a commercial CRPA's phase manifold and its gradient mapping through fairly benign roll rates. The phase pattern gradient is the delta change in phase, between two relative elements, over the change in angle-of-arrival. For example, with a simple 10 deg/s roll rate and a chosen commercial set of phase patterns, the roll induced phase rates perceived by the AJ-E are magnified by >80deg/deg phase manifold gradients for one combination of antenna elements. This 10 deg/s roll rate, magnified by the phase pattern, blurs the covariance phase estimate based on angle-of-arrival and relative per-antenna-element velocity. Each element will perceive the Doppler effects relative to the strongest jamming transmitters; this relationship is provided in the paper (“phase error” = Pi*Doppler*[integration time] = radians of phase error).
The paper also validates the closed-form relationship of Doppler (or phase-rate) changes and its effective relationship to the AJ-E's per-component covariance estimate. Through empirical methods, software derived IQ samples are generated and a covariance estimate is provided. The per-component phase errors are mapped and a resulting MUSIC-based eigen decomposition is used to quantify its resulting error contributions to the AJ weighting and its direction finding capabilities.
Also, the same IQ samples are gathered through RF recordings through the Army AMRDEC's Wavefront Integrated Threat Simulator (WITS) and a suite of jamming signals (broadband noise, continuous wave and binary phase shift keyed modulated noise). The WITS provides a 15kHz update rate with 1/3 pico-second precision and 5 pico-second resolution. WITS has been validated and the Doppler shift is demonstrated through changing delays over the varied integration periods. The WITS recorded IQ samples, gathered through a two-channel rubidium-disciplined Ettus USRP, are used to corroborate the software generated samples with included thermal noise perceived by the USRP front end.
Finally the same suite of jamming signals are provided, through the WITS, to a set of commercial AJ-E. Their estimated covariance matrices are provided as a telemetered output and examined through the given phase pattern, antenna geometry and eigen decomposition. Together, with non-Doppler-shifted estimates, a clear side-by-side validation of Doppler effects is shown and the influence on per-component phase relationships is validated.
This paper's trade-space study of Doppler provides an understanding of its influence on covariance and the effectiveness of an AJ-E. The phase pattern contributions are highlighted and its significant effect for the backlobe structure are presented. The results are validated through software, hardware recorded IQ samples and commercial AJ-E covariance matrix estimates. Together this paper provides a comprehensive examination of Doppler and the predictable effects in the AJ-E's covariance space.



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