Synthetic aperture radar: A focus on current problems

Synthetic aperture radar (SAR) is a powerful tool for mapping and remote sensing. The theory and operation of SAR have seen a period of intense activity in recent years. This paper attempts to review some of the more advanced topics studied in connection with modern SAR systems based on digital processing. Following a brief review of the principles involved in the operation of SAR, attention is focussed on special topics such as advanced SAR modelling and focussing techniques, in particular clutterlock and autofocus, Doppler centroid (DC) estimation methods involving seismic migration technique, moving target imaging, bistatic radar imaging, effects of system nonlinearities, etc.

Model track studies on fouled ballast using ground penetrating radar and multichannel analysis of surface wave

Ballast fouling is created by the breakdown of aggregates or outside contamination by coal dust from coal trains, or from soil intrusion beneath rail track. Due to ballast fouling, the conditions of rail track can be deteriorated considerably depending on the type of fouling material and the degree of fouling. So far there is no comprehensive guideline available to identify the critical degree of fouling for different types of fouling materials. This paper presents the identification of degree of fouling and types of fouling using non-destructive testing, namely seismic surface-wave and ground penetrating radar (GPR) survey. To understand this, a model rail track with different degree of fouling has been constructed in Civil engineering laboratory, University of Wollongong, Australia. Shear wave velocity obtained from seismic survey has been employed to identify the degree of fouling and types of fouling material. It is found that shear wave velocity of fouled ballast increases initially, reaches optimum fouling point (OFP), and decreases when the fouling increases. The degree of fouling corresponding after which the shear wave velocity of fouled ballast will be smaller than that of clean ballast is called the critical fouling point (CFP). Ground penetrating radar with four different ground coupled antennas (500 MHz, 800 MHz, 1.6 GHz and 2.3 GHz) was also used to identify the ballast fouling condition. It is found that the 800 MHz ground coupled antenna gives a better signal in assessing the ballast fouling condition. Seismic survey is relatively slow when compared to GPR survey however it gives quantifiable results. In contrast, GPR survey is faster and better in estimating the depth of fouling. (C) 2011 Elsevier B.V. All rights reserved.

Performance evaluation of neural network algorithms for multisensor data fusion in an airborne track while scan radar

This paper deals with the solution to the problem of multisensor data fusion for a single target scenario as detected by an airborne track-while-scan radar. The details of a neural network implementation, various training algorithms based on standard backpropagation, and the results of training and testing the neural network are presented. The promising capabilities of RPROP algorithm for multisensor data fusion for various parameters are shown in comparison to other adaptive techniques

Ganga-Brahmaputra river discharge from Jason-2 radar altimetry: An update to the long-term satellite-derived estimates of continental freshwater forcing flux into the Bay of Bengal

This paper discusses the use of Jason-2 radar altimeter measurements to estimate the Ganga-Brahmaputra surface freshwater flux into the Bay of Bengal for the period mid-2008 to December 2011. A previous estimate was generated for 1993-2008 using TOPEX-Poseidon, ERS-2 and ENVISAT, and is now extended using Jason-2. To take full advantages of the new availability of in situ rating curves, the processing scheme is adapted and the adjustments of the methodology are discussed here. First, using a large sample of in situ river height measurements, we estimate the standard error of Jason-2-derived water levels over the Ganga and the Brahmaputra to be respectively of 0.28 m and 0.19 m, or less than similar to 4% of the annual peak-to-peak variations of these two rivers. Using the in situ rating curves between water levels and river discharges, we show that Jason-2 accurately infers Ganga and Brahmaputra instantaneous discharges for 2008-2011 with mean errors ranging from similar to 2180 m(3)/s (6.5%) over the Brahmaputra to similar to 1458 m(3)/s (13%) over the Ganga. The combined Ganga-Brahmaputra monthly discharges meet the requirements of acceptable accuracy (15-20%) with a mean error of similar to 16% for 2009-2011 and similar to 17% for 1993-2011. The Ganga-Brahmaputra monthly discharge at the river mouths is then presented, showing a marked interannual variability with a standard deviation of similar to 12500 m(3)/s, much larger than the data set uncertainty. Finally, using in situ sea surface salinity observations, we illustrate the possible impact of extreme continental freshwater discharge event on the northern Bay of Bengal as observed in 2008.

Multiple transmitter localization and communication footprint identification using sparse reconstruction techniques

This paper considers the problem of identifying the footprints of communication of multiple transmitters in a given geographical area. To do this, a number of sensors are deployed at arbitrary but known locations in the area, and their individual decisions regarding the presence or absence of the transmitters' signal are combined at a fusion center to reconstruct the spatial spectral usage map. One straightforward scheme to construct this map is to query each of the sensors and cluster the sensors that detect the primary's signal. However, using the fact that a typical transmitter footprint map is a sparse image, two novel compressive sensing based schemes are proposed, which require significantly fewer number of transmissions compared to the querying scheme. A key feature of the proposed schemes is that the measurement matrix is constructed from a pseudo-random binary phase shift applied to the decision of each sensor prior to transmission. The measurement matrix is thus a binary ensemble which satisfies the restricted isometry property. The number of measurements needed for accurate footprint reconstruction is determined using compressive sampling theory. The three schemes are compared through simulations in terms of a performance measure that quantifies the accuracy of the reconstructed spatial spectral usage map. It is found that the proposed sparse reconstruction technique-based schemes significantly outperform the round-robin scheme.

A novel space cloth using resistor grid network for radar absorbers in stealth applications

We report novel resistor grid network based space cloth for application in single and multi layer radar absorbers. The space cloth is analyzed and relations are derived for the sheet resistance in terms of the resistor in the grid network. Design curves are drawn using MATLAB and the space cloth is analyzed using HFSS™ software in a Salisbury screen for S, C and X bands. Next, prediction and simulation results for a three layer Jaumann absorber using square grid resistor network with a Radar Cross Section Reduction (RCSR) of -15 dB over C, X and Ku bands is reported. The simulation results are encouraging and have led to the fabrication of prototype broadband radar absorber and experimental work is under progress.

Integration of speckle de-noising and image segmentation using synthetic aperture radar image for flood extent extraction

Flood is one of the detrimental hydro-meteorological threats to mankind. This compels very efficient flood assessment models. In this paper, we propose remote sensing based flood assessment using Synthetic Aperture Radar (SAR) image because of its imperviousness to unfavourable weather conditions. However, they suffer from the speckle noise. Hence, the processing of SAR image is applied in two stages: speckle removal filters and image segmentation methods for flood mapping. The speckle noise has been reduced with the help of Lee, Frost and Gamma MAP filters. A performance comparison of these speckle removal filters is presented. From the results obtained, we deduce that the Gamma MAP is reliable. The selected Gamma MAP filtered image is segmented using Gray Level Co-occurrence Matrix (GLCM) and Mean Shift Segmentation (MSS). The GLCM is a texture analysis method that separates the image pixels into water and non-water groups based on their spectral feature whereas MSS is a gradient ascent method, here segmentation is carried out using spectral and spatial information. As test case, Kosi river flood is considered in our study. From the segmentation result of both these methods are comprehensively analysed and concluded that the MSS is efficient for flood mapping.

Comparison of CloudSat and TRMM radar reflectivities

Comparison of reflectivity data of radars onboard CloudSat and TRMM is performed using coincident overpasses. The contoured frequency by altitude diagrams (CFADs) are constructed for two cases: (a) only include collocated vertical profiles that are most likely to be raining and (b) include all collocated profiles along with cloudy pixels falling within a distance of about 50 km from the centre point of coincidence. Our analysis shows that for both cases, CloudSat underestimates the radar reflectivity by about 10 dBZ compared to that of TRMM radar below 15 km altitude. The difference is well outside the uncertainty value of similar to 2 dBZ of each radar. Further, CloudSat reflectivity shows a decreasing trend while that of TRMM radar an increasing trend below 4 km height. Basically W-band radar that CloudSat flies suffers strong attenuation in precipitating clouds and its reflectivity value rarely exceeds 20 dBZ though its technical specification indicates the upper measurement limit to be 40 dBZ. TRMM radar, on the other hand, cannot measure values below 17 dBZ. In fact combining data from these two radars seems to give a better overall spatial structure of convective clouds.

Crevasses detection in Himalayan glaciers using ground-penetrating radar

Identification and mapping of crevasses in glaciated regions is important for safe movement. However, the remote and rugged glacial terrain in the Himalaya poses greater challenges for field data collection. In the present study crevasse signatures were collected from Siachen and Samudra Tapu glaciers in the Indian Himalaya using ground-penetrating radar (GPR). The surveys were conducted using the antennas of 250 MHz frequency in ground mode and 350 MHz in airborne mode. The identified signatures of open and hidden crevasses in GPR profiles collected in ground mode were validated by ground truthing. The crevasse zones and buried boulder areas in a glacier were identified using a combination of airborne GPR profiles and SAR data, and the same have been validated with the high-resolution optical satellite imagery (Cartosat-1) and Survey of India mapsheet. Using multi-sensor data, a crevasse map for Samudra Tapu glacier was prepared. The present methodology can also be used for mapping the crevasse zones in other glaciers in the Himalaya.

Channel estimation at the transmitter in a reciprocal MIMO spatial multiplexing system

This paper considers the problem of channel estimation at the transmitter in a spatial multiplexing-based Time Division Duplex (TDD) Multiple Input Multiple Output (MIMO) system with perfect CSIR. A novel channel-dependent Reverse Channel Training (RCT) sequence is proposed, using which the transmitter estimates the beamforming vectors for forward link data transmission. This training sequence is designed based on the following two metrics: (i) a capacity lower bound, and (ii) the mean square error in the estimate. The performance of the proposed training scheme is analyzed and is shown to significantly outperform the conventional orthogonal RCT sequence. Also, in the case where the transmitter uses water-filling power allocation for data transmission, a novel RCT sequence is proposed and optimized with respect to the MSE in estimating the transmit covariance matrix.

Secrecy in the 2-User Symmetric Deterministic Interference Channel with Transmitter Cooperation

This work presents novel achievable schemes for the 2-user symmetric linear deterministic interference channel with limited-rate transmitter cooperation and perfect secrecy constraints at the receivers. The proposed achievable scheme consists of a combination of interference cancelation, relaying of the other user's data bits, time sharing, and transmission of random bits, depending on the rate of the cooperative link and the relative strengths of the signal and the interference. The results show, for example, that the proposed scheme achieves the same rate as the capacity without the secrecy constraints, in the initial part of the weak interference regime. Also, sharing random bits through the cooperative link can achieve a higher secrecy rate compared to sharing data bits, in the very high interference regime. The results highlight the importance of limited transmitter cooperation in facilitating secure communications over 2-user interference channels.

Outer Bounds on the Secrecy Rate of the 2-User Symmetric Deterministic Interference Channel with Transmitter Cooperation

This paper derives outer bounds for the 2-user symmetric linear deterministic interference channel (SLDIC) with limited-rate transmitter cooperation and perfect secrecy constraints at the receivers. Five outer bounds are derived, under different assumptions of providing side information to receivers and partitioning the encoded message/output depending on the relative strength of the signal and the interference. The usefulness of these outer bounds is shown by comparing the bounds with the inner bound on the achievable secrecy rate derived by the authors in a previous work. Also, the outer bounds help to establish that sharing random bits through the cooperative link can achieve the optimal rate in the very high interference regime.