G-Band Radar for Humidity and Cloud Remote Sensing

K.B. Cooper, R.J. Roy, R. Dengler, R.R. Monje, M. Alonso-delPino, J.V. Siles, O. Yurduseven, C. Parashare, L. Millán, M. Lebsock

Research output: Contribution to journalArticleScientificpeer-review

17 Citations (Scopus)

Abstract

VIPR (vapor in-cloud profiling radar) is a tunable G-band radar designed for humidity and cloud remote sensing. VIPR uses all-solid-state components and operates in a frequency-modulated continuous-wave (FMCW) radar mode, offering a transmit power of 200–300 mW. Its typical chirp bandwidth of 10 MHz over a center-frequency tuning span of 167–174.8 GHz results in a nominal range resolution of 15 m. The radar’s measured noise figure over the transmit band is between 7.4 and 10.4 dB, depending on its frequency and hardware configuration, and its calculated antenna gain is 58 dB. These parameters mean that with typical 1 ms chirp times, single-pulse cloud reflectivities as low as −26 dBZ are detectable with unity signal-to-noise at 5 km. Experimentally, radar returns from ice clouds above 10 km in height have been observed from the ground. VIPR’s absolute sensitivity was validated using a spherical metal target in the radar antenna’s far-field, and a G-band switch has been implemented in an RF calibration loop for periodic recalibration. The radar achieves high sensitivity with thermal noise limited detection both by virtue of its low-noise RF architecture and by using a quasioptical duplexing method that preserves ultrahigh transmit/receive isolation despite operation in an FMCW mode with a single primary antenna shared by the transmitter and receiver.
Original languageEnglish
Article number9108406
Pages (from-to)1106-1117
Number of pages12
JournalIEEE Transactions on Geoscience and Remote Sensing
Volume59
Issue number2
DOIs
Publication statusPublished - 2020

Keywords

  • Airborne radar
  • differential absorption radar
  • meteorological radar
  • millimeter wave radar

Fingerprint

Dive into the research topics of 'G-Band Radar for Humidity and Cloud Remote Sensing'. Together they form a unique fingerprint.

Cite this