1、 Report ITU-R RS.2165(09/2009)Identification of degradation due to interference and characterization of possible interference mitigation techniques for passive sensors operating in the Earth exploration-satellite service (passive)RS SeriesRemote sensing systemsii Rep. ITU-R RS.2165 Foreword The role
2、 of the Radiocommunication Sector is to ensure the rational, equitable, efficient and economical use of the radio-frequency spectrum by all radiocommunication services, including satellite services, and carry out studies without limit of frequency range on the basis of which Recommendations are adop
3、ted. The regulatory and policy functions of the Radiocommunication Sector are performed by World and Regional Radiocommunication Conferences and Radiocommunication Assemblies supported by Study Groups. Policy on Intellectual Property Right (IPR) ITU-R policy on IPR is described in the Common Patent
4、Policy for ITU-T/ITU-R/ISO/IEC referenced in Annex 1 of Resolution ITU-R 1. Forms to be used for the submission of patent statements and licensing declarations by patent holders are available from http:/www.itu.int/ITU-R/go/patents/en where the Guidelines for Implementation of the Common Patent Poli
5、cy for ITU-T/ITU-R/ISO/IEC and the ITU-R patent information database can also be found. Series of ITU-R Reports (Also available online at http:/www.itu.int/publ/R-REP/en) Series Title BO Satellite delivery BR Recording for production, archival and play-out; film for television BS Broadcasting servic
6、e (sound) BT Broadcasting service (television) F Fixed service M Mobile, radiodetermination, amateur and related satellite services P Radiowave propagation RA Radio astronomy RS Remote sensing systems S Fixed-satellite service SA Space applications and meteorology SF Frequency sharing and coordinati
7、on between fixed-satellite and fixed service systems SM Spectrum management Note: This ITU-R Report was approved in English by the Study Group under the procedure detailed in Resolution ITU-R 1. Electronic Publication Geneva, 2010 ITU 2010 All rights reserved. No part of this publication may be repr
8、oduced, by any means whatsoever, without written permission of ITU. Rep. ITU-R RS.2165 1 REPORT ITU-R RS.2165 Identification of degradation due to interference and characterization of possible interference mitigation techniques for passive sensors operating in the Earth exploration-satellite service
9、 (passive) (2010) Scope The report is focused on radio-frequency interference (RFI) to radiometric measurements made by Earth exploration-satellites. The natural noise floor in the bands under consideration is the data being measured. The text first discusses how the measurements are used in meteoro
10、logical and climatic products. Then, it addresses the detectability of RFI and its potential impact on products. Finally, it discusses some techniques that might be used to mitigate (reduce, not eliminate) the impact from RFI. No mitigation techniques have been identified which can be applied to the
11、 microwave sensors and their products to allow RFI without degrading their performance reliability or availability. NOTE 1 References to provisions of the Radio Regulations (RR) are based on the RR Edition of 2008. TABLE OF CONTENTS Page 1 Introduction 3 1.1 Passive sensing missions 3 1.2 Content an
12、d organization of report . 3 2 Overview of passive sensing products 3 2.1 Passive sensing products . 3 2.2 Product hierarchy and descriptions . 5 2.3 Product generation process . 8 2.4 Environmental products and associated sensing bands 9 2.5 Uses of environmental products and NWP model with data as
13、similation scheme 9 2.6 Summary of passive sensing products 12 3 Product quality and RFI 12 3.1 Impact on quality 13 3.1.1 General factors affecting product quality . 13 3.1.2 Impact on products . 13 2 Rep. ITU-R RS.2165 Page 3.1.3 Propagation of errors through product levels . 14 3.1.4 RFI detectio
14、n in the NWP model . 15 3.1.5 Impact of RFI on forecasting . 15 3.2 RFI identification 17 3.2.1 Near-real time interference detection using quality control methods of weather models 17 3.2.2 Real-time and near-real-time detection of RFI by identifying non-natural properties 17 3.2.3 Technique propos
15、ed for digital RFI detector . 19 3.2.4 Post-processing interference detection . 20 3.3 Detection and impact of RFI on the mission 21 3.4 Summary of RFI detection in products . 22 4 Interference and impact 22 4.1 ITU guidance 23 4.2 Industry understanding . 23 4.3 Passive remote sensing mitigation 23
16、 4.3.1 RFI prevention through regulation . 23 4.3.2 Data elimination . 23 4.3.3 Real time mitigation techniques . 24 4.3.4 Use of redundancy for missing or corrupted data estimation 25 4.4 Mitigation of RFI risks . 25 4.5 Summary of interference and impact 25 5 Summary . 28 6 Conclusion 29 Annex A S
17、cience of passive sensing. 30 Annex B Environmental data products . 33 Annex C Acronyms . 39 Rep. ITU-R RS.2165 3 1 Introduction 1.1 Passive sensing missions The “passive sensing mission” is described as the “passive” detection and analysis of naturally occurring, ambient microwave energy (the natur
18、al noise floor from the antenna) for the purpose of determining present and future environmental conditions. Environmental products are generated from the output of these predictions. The most critical products are forecasts of weather and climate. These forecasts affect human endeavours. 1.2 Conten
19、t and organization of report Section 2 describes the meteorological and climatology products developed from the radiometric measurements and their application in numerical weather prediction (NWP). Section 3 discusses detected radio-frequency interference (RFI) in the products made from radiometric
20、measurements and the impact of RFI on weather forecasting capability. Section 4 discusses how RFI can be prevented or its impact reduced Annex A of this paper addresses the science of microwave sensing from black body radiation to the receiver measurement. This material will enhance the understandin
21、g of the sensor products and their vulnerability to RFI. Annex B presents a table that relates meteorological data products to the sensor measurements used to produce them. Annex C is a glossary of terms used in the report. 2 Overview of passive sensing products Passive sensors measure the electroma
22、gnetic energy emitted and scattered by the Earth and its atmosphere. This energy measured by the sensor varies with the equivalent blackbody temperature of the surface and energy transfers in the intervening atmospheric path. This energy appears as the natural noise floor in the band under considera
23、tion. The word “product” in this paper will refer to a range of products created from microwave measurements. These include data records of the measurements, images derived from the records, plots, forecasts, warnings, etc. However strictly speaking the product is the data record created from the me
24、asurements. The microwave radiometric measurements along with other measurements (e.g. infrared) are converted to data file products such as rain rate, sea surface temperature or soil moisture. Products can be categorized by the media they describe such as the atmosphere, ocean or land. Some of the
25、products are publicly provided while others remain in the government or private domain. Some well known weather products include: hurricane formation and path displays, atmospheric temperature profiles, and water precipitation maps. 2.1 Passive sensing products Passive sensor measurements are conver
26、ted into brightness temperatures which are mapped in space and time. These brightness temperatures are stored in digital records. In the case of polar orbiting spacecraft, these records typically represent either an entire orbit or portions thereof (Level 1 product). The science of brightness temper
27、atures and its relationship to Earth and atmospheric parameters is explained in Annex A. Mathematical algorithms are used with the combination of the brightness temperatures to provide geographic information on meteorological parameters (Level 2 products). In some level 2 products ancillary informat
28、ion is used to generate the products. Such ancillary information includes terrain type, temperature and humidity information from other sensors. 4 Rep. ITU-R RS.2165 Atmospheric temperature profiles are created from measurements using instruments operating in the 50-60 GHz frequency range. Knowing t
29、he barometric pressure and the percentage of oxygen in the atmosphere, the energy measurement of the instrument can then determine the temperature of the air. Similarly at the water vapour lines near 23 and 183 GHz, the temperature is related to other measurements, as well as the barometric pressure
30、, so the water content in the atmosphere can be determined from the measured microwave energy. Figure 1 illustrates several oceanographic and meteorological parameters and the variance of the brightness temperature for each physical parameter. A particular physical parameter is determined by applyin
31、g weighting functions or variation schemes to measurements from the several channels to remove the influence of other physical parameters. FIGURE 1 Sensitivity of physical parameters in oceanography and meteorology with respect to frequency and the optimum channels as arrow symbols* Report RS.2165-0
32、1Wind speedSalinityNormalizedradiometricsensitivity+010 20 30 40WatervapourLiquid cloudsFrequency (GHz)Sea surface temperature* http:/www.profc.udes.cl/gabriel/tutoriales/index.htm. Each physical parameter such as salinity, water vapour, wind speed, etc. has a frequency dependent influence on the br
33、ightness temperature measurements. Figure 1 is a plot of the relative change in the brightness temperature caused by the physical parameter. The arrows on the frequency axis represent channels where radiometric measurements are made. The measurements are used to characterize the curve for each physi
34、cal parameter. Rep. ITU-R RS.2165 5 The ordinate labelled Normalized Radiometric Sensitivity is Tb/Pi, where Tbis Brightness temperature and Pi is one of the geophysical parameters in the graph (for example, wind speed or sea surface temperature). Thus, the quantity represents how much brightness ch
35、anges as one of the geophysical parameter changes. For example, if brightness temperature changes 0.2 K when sea surface temperature changes by 2 K, then ratio will be 0.1. These ratios were plotted as a function of frequency to see how much this ratio is sensitive with the frequencies. The graph pr
36、ovides a visual representation through scaling of the relative values and thus no specific numerical scale is provided. 2.2 Product hierarchy and descriptions The following description applies to a particular meteorological satellite system, (e.g. National polar-orbiting operational environmental sa
37、tellite system (NPOESS), which is representative of a typical meteorological system. Two types of descriptors are in common use to describe products, one is hierarchical the other is more descriptive. Level 0, Level 1A, Level 1B and Level 2 are elements of the hierarchy used to indicate product type
38、s from raw (Level 0) to refined (Level 2). A more descriptive lexicon uses the terms raw data, raw data records (RDR), sensor data records (SDR), temperature data records (TDR) and environmental data records (EDR). Level 0: Raw data Spacecraft carry a suite of sensors designed to detect environmenta
39、l data either reflected or emitted from the earth, the atmosphere, and space. The satellites store these data and transmit the data to earth stations. These data, before being processed, are called raw data (Level 0). Level 1: Satellite data records Satellite data records, generally considered as Le
40、vel 1 data products, are the records of brightness temperatures measured in a few select frequency bands. These products can be subdivided into three data types: RDR (Level 1A) Unmodified sensors output received from the spacecraft and separated into a record specifically related to the brightness t
41、emperature measured on a specific band, where brightness temperature is defined as a measure of the intensity of radiation thermally emitted by an object, given in units of temperature. TDR (Level 1B) Antenna brightness temperature calibrated, time-tagged and earth-located. SDR (Level 1C) Antenna br
42、ightness temperatures with antenna pattern correction, calibrated, time-tagged, earth-located. Antenna pattern corrections are needed because the antenna receives radiation from the entire 4 steradians at varying directional gain values. The measurements must be adjusted to represent only the resolu
43、tion cell of the sensor. Figure 2 shows colorized images developed from satellite data records for three passive sensor bands. The left images are obtained with horizontal polarization and the right images with vertical polarization. The image bands from top to bottom are centred at 6.9 GHz, 10.7 GH
44、z and 18.7 GHz. 6 Rep. ITU-R RS.2165 FIGURE 2 Images created from satellite data records from three frequency bands and two polarizations from the AMSR-E sensor on the Aqua satellite (Note in the 6.9 GHz images in the two top panels the presence of red areas, which are RFI signals) Report RS.2165-02
45、07 H10 H18 H07 V10 V18 V50403020130 120 110 100 90 80 70 60Latitude(deg)Longitude (deg)AMSR-E TB, 6.9 GHz H-Pol220 240 260 280 300 32050403020130 120 110 100 90 80 70 60Latitude(deg)Longitude (deg)AMSR-E TB, 10.7 GHz H-Pol220 240 260 280 300 32050403020130 120 110 100 90 80 70 60Latitude(deg)Longitu
46、de (deg)AMSR-E TB, 18.7 GHz H-Pol220 240 260 280 300 32050403020130 120 110 100 90 80 70 60Latitude(deg)Longitude (deg)AMSR-E TB, 6.9 GHz V-Pol220 240 260 280 300 32050403020130 120 110 100 90 80 70 60Latitude(deg)Longitude (deg)AMSR-E TB, 18.7 GHz H-Pol220 240 260 280 300 32050403020130 120 110 100
47、 90 80 70 60Latitude(deg)Longitude (deg)AMSR-E TB, 18.7 GHz H-Pol220 240 260 280 300 320Level 2: Environmental data records Level 2 products are records of environmental or climatic parameters derived from the Level 1 brightness temperature records. Band selection for the radiometric measurements is
48、 driven by the need to interpret the measurements to retrieve the meteorological, oceanographic and land parameters. These products contain meteorological, oceanographic, and land parameters. In some cases the products are generated via a simple equation with the variables consisting of brightness t
49、emperatures. In other cases, they result from fairly sophisticated scientific understanding of radiative transfer. Figure 3 is a visualization of a meteorological product made from satellite microwave data. This shows the depth of water/unit area which would result from condensing all the water vapour in the atmosphere in a unit column. Weather, climate, environmental forecasting and archiving products These products are made from the environmental data records with the use of computer models or visual i
