Characterization of urban ground clutter with new generation airborne Doppler weather radar

Mackenzie, Anne I.; Baxa, E. G.; Harrah, Steven

doi:10.1109/nrc.1993.270495

Cited by 2 publications

(2 citation statements)

References 4 publications

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“…where P r is the received power, P t is the transmitted power, τ is the temporal duration of a pulse, G is the gain of the transmitting antenna, λ indicates the radar wavelength, θ is the beam width (in radians), c is the speed of light, and η (in dB km) is the radar cross section (RCS) of the target area (Mackenzie et al, 1993). R is the distance from the transmitter to the target area.…”

Section: The Weather Radarmentioning

confidence: 99%

“…Naturally, due to both environment and technological limitations, the estimates from such sources may have high levels of uncertainty and errors (e.g. Mackenzie et al, 1993). For meteorologists and hydrologists attempting to use this information to either better understand storm dynamics or to inform infrastructure planning, each of these methods has unique information.…”

Section: Introductionmentioning

confidence: 99%

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New algorithm for integration between wireless microwave sensor network and radar for improved rainfall measurement and mapping

et al. 2014

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Abstract. One of the main challenges for meteorological and hydrological modelling is accurate rainfall measurement and mapping across time and space. To date, the most effective methods for large-scale rainfall estimates are radar, satellites, and, more recently, received signal level (RSL) measurements derived from commercial microwave networks (CMNs). While these methods provide improved spatial resolution over traditional rain gauges, they have their limitations as well. For example, wireless CMNs, which are comprised of microwave links (ML), are dependant upon existing infrastructure and the ML' arbitrary distribution in space. Radar, on the other hand, is known in its limitation for accurately estimating rainfall in urban regions, clutter areas and distant locations. In this paper the pros and cons of the radar and ML methods are considered in order to develop a new algorithm for improving rainfall measurement and mapping, which is based on data fusion of the different sources. The integration is based on an optimal weighted average of the two data sets, taking into account location, number of links, rainfall intensity and time step. Our results indicate that, by using the proposed new method, we not only generate more accurate 2-D rainfall reconstructions, compared with actual rain intensities in space, but also the reconstructed maps are extended to the maximum coverage area. By inspecting three significant rain events, we show that our method outperforms CMNs or the radar alone in rain rate estimation, almost uniformly, both for instantaneous spatial measurements, as well as in calculating total accumulated rainfall. These new improved 2-D rainfall maps, as well as the accurate rainfall measurements over large areas at sub-hourly timescales, will allow for improved understanding, initialization, and calibration of hydrological and meteorological models mainly necessary for water resource management and planning.

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Section: The Weather Radarmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

New algorithm for integration between wireless microwave sensor network and radar for improved rainfall measurement and mapping

et al. 2014

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New signal processing developments in the detection of low-altitude windshear with airborne Doppler radar

Baxa

Lai

Kunkel³

The Record of the 1993 IEEE National Radar Conference

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Airborne weather radar Is being developed to detect hazardous low altitude windstmar which has been a major contributing factor in many airline crashes In this country. One of the major challenges is development of signal processing algorithms which will perform satisfactorily when the weather return signal power to Interfering ground clutter return power is very low. This paper describes two basic approaches which are under Investigation. One approach is to estimate windspeed from the radar returns using an extended Prony based method without a clutter rejection pre-filter, since the fllterlng process itself can reduce the weather signal below useful Isvels. Alternatively, improved clutter pre-filtering techniques are being iwestigated based on an adaptive noise canceller implementaticm of the LMS algorithm. Results are presented to illustrate some of the capabilities of each. Also described is a method for merging flight experimental clutter return data with a simulated microburst return based on a radar measured windfield. This allows very rare low reflectivity weather events to be studied in the presence of actual clutter data.

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Characterization of urban ground clutter with new generation airborne Doppler weather radar

Cited by 2 publications

References 4 publications

New algorithm for integration between wireless microwave sensor network and radar for improved rainfall measurement and mapping

New algorithm for integration between wireless microwave sensor network and radar for improved rainfall measurement and mapping

New signal processing developments in the detection of low-altitude windshear with airborne Doppler radar

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