Synthetic Aperture Radar (SAR) data processing

The available and optimal methods for generating SAR imagery for NASA applications were identified. The SAR image quality and data processing requirements associated with these applications were studied. Mathematical operations and algorithms required to process sensor data into SAR imagery were defined. The architecture of SAR image formation processors was discussed, and technology necessary to implement the SAR data processors used in both general purpose and dedicated imaging systems was addressed

Performance-Optimized Quantization for SAR and InSAR Applications

For the design of present and next-generation spaceborne SAR missions, constantly increasing data rates are being demanded, which impose stringent requirements in terms of onboard memory and downlink capacity. In this scenario, the efficient quantization of SAR raw data is of primary importance since the utilized compression rate is directly related to the volume of data to be stored and transmitted to the ground, and at the same time, it affects the resulting SAR imaging performance. In this article, we introduce the performance-optimized block-adaptive quantization (PO-BAQ), a novel approach for SAR raw data compression that aims at optimizing the resource allocation and, at the same time, the quality of the resulting SAR and InSAR products. This goal is achieved by exploiting the a priori knowledge of the local SAR backscatter statistics, which allows for the generation of high-resolution bitrate maps that can be employed to fulfill a predefined performance requirement. Analyses of experimental TanDEM-X interferometric data are presented, which demonstrates the potential of the proposed method as a helpful tool for performance budget definition and data rate optimization of present and future SAR missions

A Mobile, Multichannel, UWB Radar for Potential Ice Core Drill Site Identification in East Antarctica: Development and First Results

We developed a high-performance, multichannel, ultra-wideband radar system for measurements of the base and interior of the East Antarctic Ice Sheet. We designed the radar to be of high power (4000-W peak) yet portable and to be able to operate with 60-MHz bandwidth at a center frequency of 200 MHz, providing high sensitivity and fine vertical resolution relative to current technology. We used the radar to perform extensive measurements as a part of a multinational collaboration. We collected data onboard a tracked vehicle outfitted with an array of high-gain antennas. We sounded 2- to 3-km thick ice near Dome Fuji. Preliminary ice thickness data match those obtained via semicoincident measurements performed with a different surface-based pulse-modulated radar system operated during the same field campaign, as well as previous airborne measurements. In addition, we mapped internal reflection horizons with fine vertical resolution from 300 m below the ice surface to ~100 m above the bed. In this article, we provide a detailed overview of the radar instrument design, implementation, and field measurement setup. We present sample data to illustrate its capabilities and discuss how the data collected with it will be valuable for the assessment of promising drilling sites to recover ice cores that are 0.9-1.5 million years old

A Mobile, Multichannel, UWB Radar for Potential Ice Core Drill Site Identification in East Antarctica: Development and First Results

We developed a high-performance, multichannel, ultra-wideband radar system for measurements of the base and interior of the East Antarctic Ice Sheet. We designed the radar to be of high power (4000-W peak) yet portable and to be able to operate with 60-MHz bandwidth at a center frequency of 200 MHz, providing high sensitivity and fine vertical resolution relative to current technology. We used the radar to perform extensive mea- surements as a part of a multinational collaboration. We collected data onboard a tracked vehicle outfitted with an array of high-gain antennas. We sounded 2- to 3-km thick ice near Dome Fuji. Prelim- inary ice thickness data match those obtained via semicoincident measurements performed with a different surface-based pulse- modulated radar system operated during the same field campaign, as well as previous airborne measurements. In addition, we mapped internal reflection horizons with fine vertical resolution from 300 m below the ice surface to ∼100 m above the bed. In this article, we provide a detailed overview of the radar instrument design, implementation, and field measurement setup. We present sample data to illustrate its capabilities and discuss how the data collected with it will be valuable for the assessment of promising drilling sites to recover ice cores that are 0.9–1.5 million years old

Processing of Multichannel Remote-Sensing Images with Prediction of Performance Parameters

In processing of multichannel remote sensing data, there is a need in automation of basic operations as filtering and compression. Automation presumes undertaking a decision on expedience of image filtering. Automation also deals with obtaining of information based on which certain decisions can be undertaken or parameters of processing algorithms can be chosen. For the considered operations of denoising and lossy compression, it is shown that their basic performance characteristics can be quite easily predicted based on easily calculated local statistics in discrete cosine transform (DCT) domain. The described methodology of prediction is shown to be general and applicable to different types of noise under condition that its basic characteristics are known in advance or pre-estimated accurately

The Space and Earth Science Data Compression Workshop

This document is the proceedings from a Space and Earth Science Data Compression Workshop, which was held on March 27, 1992, at the Snowbird Conference Center in Snowbird, Utah. This workshop was held in conjunction with the 1992 Data Compression Conference (DCC '92), which was held at the same location, March 24-26, 1992. The workshop explored opportunities for data compression to enhance the collection and analysis of space and Earth science data. The workshop consisted of eleven papers presented in four sessions. These papers describe research that is integrated into, or has the potential of being integrated into, a particular space and/or Earth science data information system. Presenters were encouraged to take into account the scientists's data requirements, and the constraints imposed by the data collection, transmission, distribution, and archival system

Remote Sensing Data Compression

A huge amount of data is acquired nowadays by different remote sensing systems installed on satellites, aircrafts, and UAV. The acquired data then have to be transferred to image processing centres, stored and/or delivered to customers. In restricted scenarios, data compression is strongly desired or necessary. A wide diversity of coding methods can be used, depending on the requirements and their priority. In addition, the types and properties of images differ a lot, thus, practical implementation aspects have to be taken into account. The Special Issue paper collection taken as basis of this book touches on all of the aforementioned items to some degree, giving the reader an opportunity to learn about recent developments and research directions in the field of image compression. In particular, lossless and near-lossless compression of multi- and hyperspectral images still remains current, since such images constitute data arrays that are of extremely large size with rich information that can be retrieved from them for various applications. Another important aspect is the impact of lossless compression on image classification and segmentation, where a reasonable compromise between the characteristics of compression and the final tasks of data processing has to be achieved. The problems of data transition from UAV-based acquisition platforms, as well as the use of FPGA and neural networks, have become very important. Finally, attempts to apply compressive sensing approaches in remote sensing image processing with positive outcomes are observed. We hope that readers will find our book useful and interestin

Real time speaker recognition using MFCC and VQ

Speaker Recognition is a process of automatically recognizing who is speaking on the basis of the individual information included in speech waves. Speaker Recognition is one of the most useful biometric recognition techniques in this world where insecurity is a major threat. Many organizations like banks, institutions, industries etc are currently using this technology for providing greater security to their vast databases.Speaker Recognition mainly involves two modules namely feature extraction and feature matching. Feature extraction is the process that extracts a small amount of data from the speaker’s voice signal that can later be used to represent that speaker. Feature matching involves the actual procedure to identify the unknown speaker by comparing the extracted features from his/her voice input with the ones that are already stored in our speech database.In feature extraction we find the Mel Frequency Cepstrum Coefficients, which are based on the known variation of the human ear’s critical bandwidths with frequency and these, are vector quantized using LBG algorithm resulting in the speaker specific codebook. In feature matching we find the VQ distortion between the input utterance of an unknown speaker and the codebooks stored in our database. Based on this VQ distortion we decide whether to accept/reject the unknown speaker’s identity. The system I implemented in my work is 80% accurate in recognizing the correct speaker.In second phase we implement on the acoustic of Real Time speaker ecognition using mfcc and vq on a TMS320C6713 DSP board. We analyze the workload and identify the most timeconsuming operations

Communication Subsystems for Satellite Design

The objective of this chapter is to provide a comprehensive end-to-end overview of existing communication subsystems residing on both the satellite bus and payloads. These subsystems include command and mission data handling, telemetry and tracking, and the antenna payloads for both command, telemetry and mission data. The function of each subsystem and the relationships to the others will be described in detail. In addition, the recent application of software defined radio (SDR) to advanced satellite communication system design will be looked at with applications to satellite development, and the impacts on how SDR will affect future satellite missions are briefly discussed