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Since the Alpex Campaign, when 3 Stratosphere-Troposphere (ST) radar operated in Camarque as a cooperative effort of the Aeronomy Laboratory of NOAA, CO, and LSEET from Toulon, a 50 MHz Very High Frequency (VHF) ST radar was developed, improved, and tested. The operating characteristics, main objectives, preliminary results, and future experiment costs of the VHF ST radar are discussed.
The purpose of this project was research and development of an automobile collision avoidance radar system. The major finding was that the application of radar to the automobile collision avoidance problem deserves continued research even though the specific approach investigated in this effort did not perform adequately in its angle measurement capability. Additional findings were that: (1) preliminary performance requirements of a candidate radar system are not unreasonable; (2) the number and severity of traffic accidents could be reduced by using a collision avoidance radar system which observes a fairly wide (at least + or - 10 deg) field of view ahead of the vehicle; (3) the health radiation hazards of a probable radar design are not significant even when a large number of radar-equipped vehicles are considered; (4) effects of inclement weather on radar operation can be accommodated in most cases; (5) the phase monopulse radar technique as implemented demonstrated inferior angle measurement performance which warrants the recommendation of investigating alternative radar techniques; and (6) extended target and multipath effects, which presumably distort the amplitude and phase distribution across the antenna aperture, are responsible for the observed inadequate phase monopulse radar performance.
NASA's planned SMAP mission will utilize a radar operating in a band centered on 1.26 GHz and a co-observing radiometer operating at 1.41 GHz to measure surface soil moisture. Both the radar and radiometer sub-systems are susceptible to radio frequency interference (RFI). Any significant impact of such interference requires mitigation in order to avoid degradation in the SMAP science products. Studies of RFT detection and mitigation methods for both the radar and radiometer are continuing in order to assess the risk to mission products and to refine the performance achieved.
An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quasi-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well-managed watershed in southwest Oklahoma. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.
On April 27, 2011, the southeastern United States was raked with several episodes of severe weather. Numerous tornadoes caused extensive damage, and tragically, the deaths of over 300 people. In Alabama alone, there were 61 confirmed tornados, 4 of them produced EF5 damage, and several were on the ground an hour or more with continuous damage tracks exceeding 80km. The use of Doppler radars covering the region provided reflectivity and velocity signatures that allowed forecasters to monitors the severe storms from beginning to end issuing hundreds of severe weather warnings throughout the day. Meteorologists from the the NWS performed extensive surveys to assess the intensity, duration, and ground track of tornadoes reported during the event. Survey activities included site visits to the affected locations, analysis of radar and satellite data, aerial surveys, and interviews with eyewitnesses. Satellite data from NASA's MODIS and ASTER instruments played a helpful role in determining the location of tornado damage paths and in the assessment. High resolution multispectral and temporal composites helped forecasters corroborate their damage assessments, determine starting and ending points for tornado touchdowns, and helped to provide forecasters with a better big-picture view of the damage region. The imagery also helped to separate damage from the April 27th tornados from severe weather that occurred earlier that month. In a post analysis of the outbreak, tornado damage path signatures observed in the NASA satellite data have been correlated to "debris ball" signatures in the NWS Doppler radars and a special ARMOR dual-polarization radar operated by the University of Alabama Huntsville during the event. The Doppler radar data indicates a circular enhanced reflectivity signal and rotational couplet in the radial velocity likely associated with the tornado that is spatially correlated with the damage tracks in the observed satellite data. An algorithm to detect and isolate the "debris ball" from precipitation signatures in the dual polarization radar data has been developed and verified using the NASA damage track data.
For many years, the NASA Orbital Debris Program Office (ODPO) has partnered with the U.S. Department of Defense and the Massachusetts Institute of Technology Lincoln Laboratory (MIT/LL) to collect data on the orbital debris environment using the Haystack radar. These measurements are used to characterize the small debris environment in low Earth orbit (LEO), down to a noise-limited size of approximately 5 mm—depending on altitude. The Haystack radar operated by MIT Lincoln Lab underwent upgrades starting in May 2010, with operations resuming in 2014 as the Haystack Ultra-wideband Satellite Imaging Radar (HUSIR). Hence, the data collected beginning in 2014 represents the first dataset available from this upgraded sensor. HUSIR is the primary source of data used by the ODPO to statistically sample orbital debris in the 5-mm to 10-cm size regime in LEO and is a key source of data to build and validate the NASA Orbital Debris Engineering Model. In this paper, we will present recent results from measurements performed during the US Government fiscal years 2014 – 2017. Using the NASA Size Estimation Model, a method based on laboratory radar measurements of debris, we will compare the size distributions of selected orbital debris populations over this 4-year period and flux measurements of orbital debris greater than 1 cm.
For many years, the NASA Orbital Debris Program Office (ODPO) has partnered with the U.S. Department of Defense and the Massachusetts Institute of Technology Lincoln Laboratory (MIT/LL) to collect data on the orbital debris environment using the Haystack radar. These measurements are used to characterize the small debris environment in low Earth orbit (LEO), down to a noise-limited size of approximately 5 mm—depending on altitude. The Haystack radar operated by MIT/LL underwent upgrades starting in May 2010, with operations resuming in 2014 as the Haystack Ultra-wideband Satellite Imaging Radar (HUSIR). HUSIR is the primary source of data used by the ODPO to statistically sample orbital debris in the 5-mm to 10-cm size regime in LEO and is a key source of data to build and validate the NASA Orbital Debris Engineering Model. In this presentation, we will present recent HUSIR results and show how NASA uses them to understand the orbital debris environment.
A meteorological radar calibration technique is developed. It is found that the integrated, range corrected, received power saturates under intense rain conditions in a manner analogous to that encountered for the radiometric path temperature. Furthermore, it is found that this saturation condition establishes a bound which may be used to determine an absolution radar calibration for the case of radars operating at attenuating wavelengths. In the case of less intense rainfall or for radars at nonattenuating wavelengths, the relationship for direct calibration in terms of an independent measurement of radiometric path temperature is developed. This approach offers the advantage that the calibration is in terms of an independent measurement of the rainfall through the same elevated region as that viewed by the radar.
An algorithm based on a fit of the single-scattering Integral Equation Method (IEM) was developed to provide estimation of soil moisture and surface roughness parameter (a combination of rms roughness height and surface power spectrum) from quad-polarized synthetic aperture radar (SAR) measurements. This algorithm was applied to a series of measurements acquired at L-band (1.25 GHz) from both AIRSAR (Airborne Synthetic Aperture Radar operated by the Jet Propulsion Laboratory) and SIR-C (Spaceborne Imaging Radar-C) over a well- managed watershed in southwest Oklahoma. Prior to its application for soil moisture inversion, a good agreement was found between the single-scattering IEM simulations and the L band measurements of SIR-C and AIRSAR over a wide range of soil moisture and surface roughness conditions. The sensitivity of soil moisture variation to the co-polarized signals were then examined under the consideration of the calibration accuracy of various components of SAR measurements. It was found that the two co-polarized backscattering coefficients and their combinations would provide the best input to the algorithm for estimation of soil moisture and roughness parameter. Application of the inversion algorithm to the co-polarized measurements of both AIRSAR and SIR-C resulted in estimated values of soil moisture and roughness parameter for bare and short-vegetated fields that compared favorably with those sampled on the ground. The root-mean-square (rms) errors of the comparison were found to be 3.4% and 1.9 dB for soil moisture and surface roughness parameter, respectively.
A proposed effort within NASA called (ASHE) over the past few years was aimed at studying the genesis of tropical disturbances off the east coast of Africa. This effort was focused on using an instrumented Global Hawk UAV with high altitude (%Ok ft) and long duration (30 h) capability. While the Global Hawk availability remains uncertain, development of two relevant instruments, a Doppler radar (URAD - UAV Radar) and a backscatter lidar (CPL-UAV - Cloud Physics Lidar), are in progress. The radar to be discussed here is based on two previous high-altitude, autonomously operating radars on the NASA ER-2 aircraft, the ER-2 Doppler Radar (EDOP) at X-band (9.6 GHz), and the Cloud Radar System (CRS) at W- band (94 GHz). The nadir-pointing EDOP and CRS radars profile vertical reflectivity structure and vertical Doppler winds in precipitation and clouds, respectively. EDOP has flown in all of the CAMEX flight series to study hurricanes over storms such as Hurricanes Bonnie, Humberto, Georges, Erin, and TS Chantal. These radars were developed at Goddard over the last decade and have been used for satellite algorithm development and validation (TRMM and Cloudsat), and for hurricane and convective storm research. We describe here the development of URAD that will measure wind and reflectivity in hurricanes and other weather systems from a top down, high-altitude view. URAD for the Global Hawk consists of two subsystems both of which are at X-band (9.3-9.6 GHz) and Doppler: a nadir fixed-beam Doppler radar for vertical motion and precipitation measurement, and a Conical scanning radar for horizontal winds in cloud and at the surface, and precipitation structure. These radars are being designed with size, weight, and power consumption suitable for the Global Hawk and other UAV's. The nadir radar uses a magnetron transmitter and the scanning radar uses a TWT transmitter. With conical scanning of the radar at a 35" incidence angle over an ocean surface in the absence of precipitation, the surface return over a single 360 degree sweep over -25 h-diameter region provides information on the surface wind speed and direction within the scan circle. In precipitation regions, the conical scan with appropriate mapping and analysis provides the 3D structure of reflectivity beneath the plane and the horizontal winds. The use of conical scanning in hurricanes has recently been demonstrated for measuring inner core winds with the IWRAP system flying on the NOAA P3's. In this presentation, we provide a description of the URAD system hardware, status, and future plans. In addition to URAD, NASA SBIR activity is supporting a Phase I study by Remote Sensing Solutions and the University of Massachusetts for a dual-frequency IWRAP for a high altitude UAV that utilizes solid state transmitters at 14 and 35 GHz, the same frequencies that are planned for the radar on the Global Precipitation System satellite. This will be discussed elsewhere at the meeting.
The Meteoroid Input Function (MIF) model has been developed with the purpose of understanding the temporal and spatial variability of the meteoroid impact in the atmosphere. This model includes the assessment of potential observational biases, namely through the use of empirical measurements to characterize the minimum detectable radar cross-section (RCS) for the particular High Power Large Aperture (HPLA) radar utilized. This RCS sensitivity threshold allows for the characterization of the radar system s ability to detect particles at a given mass and velocity. The MIF has been shown to accurately predict the meteor detection rate of several HPLA radar systems, including the Arecibo Observatory (AO) and the Poker Flat Incoherent Scatter Radar (PFISR), as well as the seasonal and diurnal variations of the meteor flux at various geographic locations. In this paper, the MIF model is used to predict several properties of the meteors observed by the Middle and Upper atmosphere (MU) radar, including the distributions of meteor areal density, speed, and radiant location. This study offers new insight into the accuracy of the MIF, as it addresses the ability of the model to predict meteor observations at middle geographic latitudes and for a radar operating frequency in the low VHF band. Furthermore, the interferometry capability of the MU radar allows for the assessment of the model s ability to capture information about the fundamental input parameters of meteoroid source and speed. This paper demonstrates that the MIF is applicable to a wide range of HPLA radar instruments and increases the confidence of using the MIF as a global model, and it shows that the model accurately considers the speed and sporadic source distributions for the portion of the meteoroid population observable by MU.
A very-fine-range resolution Frequency Modulated-Continuous Wave radar, operating at X-band, was used to evaluate the primary backscattering contributors to the radar signal from a tall-grass prairie. Defoliation was used to help measure relative backscatter from various components of the canopy with both linear polarizations and at 30 deg and 50 deg incidence angles. Variation of the average returned power with incidence angle was greatest for the natural prairie at horizontal polarization and was the least for vertical polarization. Vertical polarization seemed to be more sensitive to the upper portions of the plants, whereas horizontal polarization was to the lower portions. Attenuation for horizontal polarization was only half that for vertical polarization. Dielectric measurements of the grass and some of the canopy components were conducted as well.
A three-dimensional imaging radar operating at high frequency e.g., 670 GHz, is disclosed. The active target illumination inherent in radar solves the problem of low signal power and narrow-band detection by using submillimeter heterodyne mixer receivers. A submillimeter imaging radar may use low phase-noise synthesizers and a fast chirper to generate a frequency-modulated continuous-wave (FMCW) waveform. Three-dimensional images are generated through range information derived for each pixel scanned over a target. A peak finding algorithm may be used in processing for each pixel to differentiate material layers of the target. Improved focusing is achieved through a compensation signal sampled from a point source calibration target and applied to received signals from active targets prior to FFT-based range compression to extract and display high-resolution target images. Such an imaging radar has particular application in detecting concealed weapons or contraband.
The primary function of the TRMM Ground Validation (GV) Program is to create GV rainfall products that provide basic validation of satellite-derived precipitation measurements for select primary sites. A fundamental and extremely important step in creating high-quality GV products is radar data quality control. Quality control (QC) processing of TRMM GV radar data is based on some automated procedures, but the current QC algorithm is not fully operational and requires significant human interaction to assure satisfactory results. Moreover, the TRMM GV QC algorithm, even with continuous manual tuning, still can not completely remove all types of spurious echoes. In an attempt to improve the current operational radar data QC procedures of the TRMM GV effort, an intercomparison of several QC algorithms has been conducted. This presentation will demonstrate how various radar data QC algorithms affect accumulated radar rainfall products. In all, six different QC algorithms will be applied to two months of WSR-88D radar data from Melbourne, Florida. Daily, five-day, and monthly accumulated radar rainfall maps will be produced for each quality-controlled data set. The QC algorithms will be evaluated and compared based on their ability to remove spurious echoes without removing significant precipitation. Strengths and weaknesses of each algorithm will be assessed based on, their abilit to mitigate both erroneous additions and reductions in rainfall accumulation from spurious echo contamination and true precipitation removal, respectively. Contamination from individual spurious echo categories will be quantified to further diagnose the abilities of each radar QC algorithm. Finally, a cost-benefit analysis will be conducted to determine if a more automated QC algorithm is a viable alternative to the current, labor-intensive QC algorithm employed by TRMM GV.
The Tropical Rainfall Measurement Mission (TRMM), a joint mission between the U.S. NASA and the Japans NASDA (National Space Development Agency), was successfully launched in November of 1997. On board of the TRMM satellite are two major microwave sensors, a real-aperture radar operating at 13.8 GHz, called the Precipitation Radar (PR), and a microwave radiometer system called TRMM Microwave Imager (TMI). The TMI contains five frequencies, ranging from 10.7 to 85 GHz, is designed to cover a wide dynamic range of rain intensities. The TMI measures the rain from the emission properties while the PR's measurement is based on the scattering of the hydrometeor. The two instruments aboard the same platform provide a complementary and synergistic measurement of precipitation. This paper will focus primarily on the TMI. The advent of microwave sensor technology in recent years, the addition of a new frequency (at 10.7 GHz), as well as the mission design, have enabled the TMI to be a superior instrument for the precipitation measurement. We will provide a description of the instrument together with some of its the design rationales and practical hardware implementation. We will also show the performance of TMI aboard the TRMM and some examples of its data.
The results from an airborne radar radiometer experiment of rainfall measurement in tropical storms are presented. The experiment was conducted in the Western Pacific in September 1990 with the NASA/DC-8 aircraft which was equipped with a nadir-loking dual-frequency rain radar operating at X band and Ka band, and several channels of microwave radiometers. The X-band radar has a capability of dual-polarization reception which enables the measurements of Linear Depolarization Ratio (LDR). The data of the microwave radiometers are compared with the radar data.
The orbital SAR (synthetic aperture radar) simulation data was used in several simulation efforts directed toward advanced SAR development. Efforts toward simulating an operational radar, simulation of antenna polarization effects, and simulation of SAR images at serveral different wavelengths are discussed. Avenues for improvements in the orbital SAR simulation and its application to the development of advanced digital radar data processing schemes are indicated.
The building of the NASA Orbital Debris Engineering Model, whether ORDEM2000 or its recently updated version ORDEM2010, uses as its foundation a number of model debris populations, each truncated at a minimum object-size ranging from 10 micron to 1 m. This paper discusses the development of the ORDEM2010 model debris populations in LEO (low Earth orbit), focusing on centimeter (smaller than 10 cm) and millimeter size regimes. Primary data sets used in the statistical derivation of the cm- and mm-size model populations are from the Haystack radar operated in a staring mode. Unlike cataloged objects of sizes greater than approximately 10 cm, ground-based radars monitor smaller-size debris only in a statistical manner instead of tracking every piece. The mono-static Haystack radar can detect debris as small as approximately 5 mm at moderate LEO altitudes. Estimation of millimeter debris populations (for objects smaller than approximately 6 mm) rests largely on Goldstone radar measurements. The bi-static Goldstone radar can detect 2- to 3-mm objects. The modeling of the cm- and mm-debris populations follows the general approach to developing other ORDEM2010-required model populations for various components and types of debris. It relies on appropriate reference populations to provide necessary prior information on the orbital structures and other important characteristics of the debris objects. NASA's LEO-to-GEO Environment Debris (LEGEND) model is capable of furnishing such reference populations in the desired size range. A Bayesian statistical inference process, commonly adopted in ORDEM2010 model-population derivations, changes a priori distribution into a posteriori distribution and thus refines the reference populations in terms of data. This paper describes key elements and major steps in the statistical derivations of the cm- and mm-size debris populations and presents results. Due to lack of data for near 1-mm sizes, the model populations of 1- to 3.16-mm objects are an empirical extension from larger debris. The extension takes into account the results of micro-debris (from 10 micron to 1 mm) population modeling that is based on shuttle impact data, in the hope of making a smooth transition between micron and millimeter size regimes. This paper also includes a brief discussion on issues and potential future work concerning the analysis and interpretation of Goldstone radar data.