A Frequency Diversity Algorithm for Extending the Radar Doppler Velocity Nyquist Interval

• Published in: IEEE transactions on aerospace and electronic systems 2020-06, Vol.56 (3), p.2462-2470
• Main Authors: Venkatesh, Vijay, Li, Lihua, McLinden, Matthew, Coon, Michael, Heymsfield, Gerald M., Tanelli, Simone, Hovhannisyan, Hayk
• Format: Article
• Language: English
• Subjects: Aerodynamics; Algorithm design; Algorithms; Avionics; Cirrus clouds; Communications And Radar; Computer simulation; data analysis; Doppler effect; Doppler radar; Doppler velocity; Echoes; Frequency diversity; Millimeter wave radar; Monte Carlo simulation; pulse-pair; Radar; Radar equipment; Radar remote sensing; Remote sensing; signal processing; Signal processing algorithms; Space flight; Time lag; Velocity
• ISSN: 0018-9251; 1557-9603
• DOI: 10.1109/TAES.2019.2958191

Compact millimeter wavelength radars have been widely used for applications such as remote sensing of clouds, guidance avionics, and recently, automotive navigation. However, the short wavelength of these radars limits their maximum unambiguous Doppler velocity. A common solution to this problem is to subsequently unfold the Doppler velocity estimate with the staggered pulse repetition time (PRT) algorithm, which requires two different PRTs to be employed in sequence. This article investigates a potentially more rapid method to extend the Doppler velocity Nyquist interval. We estimate Doppler velocity using a pair of frequency diverse pulses separated by a time lag that is significantly shorter than the PRT. During the first PRT, two pulses with center frequencies f_1, followed by f_2, separated by a lag \tau are transmitted. During the next PRT, the pulses transmitted are in the order f_2 followed by f_1. Doppler velocity is then estimated using the sum of the Doppler phases derived from f_1/f_2 and f_2/f_1 sequences. The focus of this article is the demonstration of this algorithm in a beam-filled scenario and the error canceling algorithm design. Based on Monte-Carlo simulations and data collected with the NASA Goddard Space Flight center's Cloud Radar System, the algorithm is demonstrated on nearly static surface echoes. Projected aircraft speeds and traditional pulse-pair estimates are employed as references. The algorithm was found to perform adequately on surface echoes for a low spectrum width of the order of 0.5 m/s and SNR comparable to 20 dB. Doppler velocity retrievals in a cirrus cloud layer with low velocity turbulence retained some qualitative structure, albeit with significantly degraded precision due to the lost coherence.