Several Synthetic Aperture Radar Research Articles

An Efficient Channel Imbalance Estimation Method Based on Subadditivity of Linear Normed Space of Sub-Band Spectrum for Azimuth Multichannel SAR

Azimuth multichannel (AMC) technology is one of the mainstream technical approaches to realize high-resolution wide-swath (HRWS) imaging. It has been successfully applied to several synthetic aperture radar (SAR) satellites in orbit. However, the inevitable imbalance between channels can seriously affect the azimuth reconstruction spectrum, introducing ghost targets into the final imaging results and degrading the SAR image quality. In order to address this issue, this paper proposes a channel imbalance estimation method based on minimizing the sum of the sub-band norm (MSSBN) for the reconstructed azimuth spectrum. First, the amplitude imbalance is calibrated in the range-Doppler domain. Then, the echo in each channel with phase imbalances is reconstructed by filters separately and converted to the range-Doppler domain. Finally, the global optimization algorithm is used to find the phase error of each channel so that the reconstructed postcompensation spectrum has the smallest sub-band spectrum norm sum. By two-dimensional blocking, this method can also estimate the space-varying phase imbalance in the range dimension and the time-varying phase imbalance in the azimuth dimension. Experimental results using simulated and actual AMC SAR data from the GF-3 system validate the proposed algorithm’s high estimation accuracy and excellent computational efficiency.

DETER-R: An Operational Near-Real Time Tropical Forest Disturbance Warning System Based on Sentinel-1 Time Series Analysis

Continuous monitoring of forest disturbance on tropical forests is a fundamental tool to support proactive preservation actions and to stop further destruction of native vegetation. Currently most of the monitoring systems in operation are based on optical imagery, and thus are flaw-prone on areas with frequent cloud cover. As this, several Synthetic Aperture Radar (SAR)-based systems have been developed recently, aiming all-weather disturbance detection. This article presents the main aspects and the results of the first year of operation of the SAR based Near Real-Time Deforestation Detection System (DETER-R), an automated deforestation detection system focused on the Brazilian Amazon. DETER-R uses the Google Earth Engine platform to preprocess and analyze Sentinel-1 SAR time series. New images are treated and analyzed daily. After the automated analysis, the system vectorizes clusters of deforested pixels and sends the corresponding polygons to the environmental enforcement agency. After 12 months of operational life, the system has produced 88,572 forest disturbance warnings. Human validation of the warning polygons showed a extremely low rate of misdetections, with less than 0.2% of the detected area corresponding to false positives. During the first year of operation, DETER-R provided 33,234 warnings of interest to national monitoring agencies which were not detected by its optical counterpart DETER in the same period, corresponding to an area of 105,238.5 ha, or approximately 5% of the total detections. During the rainy season, the rate of additional detections increased as expected, reaching 8.1%.

Assessment of RISAT-1 and Radarsat-2 for Sea Ice Observations from a Hybrid-Polarity Perspective

Utilizing several Synthetic Aperture Radar (SAR) missions will provide a data set with higher temporal resolution. It is of great importance to understand the difference between various available sensors and polarization modes and to consider how to homogenize the data sets for a following combined analysis. In this study, a uniform and consistent analysis across different SAR missions is carried out. Three pairs of overlapping hybrid- and full-polarimetric C-band SAR scenes from the Radar Imaging Satellite-1 (RISAT-1) and Radarsat-2 satellites are used. The overlapping Radarsat-2 and RISAT-1 scenes are taken close in time, with a relatively similar incidence angle covering sea ice in the Fram Strait and Northeast Greenland in September 2015. The main objective of this study is to identify the similarities and dissimilarities between a simulated and a real hybrid-polarity (HP) SAR system. The similarities and dissimilarities between the two sensors are evaluated using 13 HP features. The results indicate a similar separability between the sea ice types identified within the real HP system in RISAT-1 and the simulated HP system from Radarsat-2. The HP features that are sensitive to surface scattering and depolarization due to volume scattering showed great potential for separating various sea ice types. A subset of features (the second parameter in the Stokes vector, the ratio between the HP intensity coefficients, and the α s angle) were affected by the non-circularity property of the transmitted wave in the simulated HP system across all the scene pairs. Overall, the best features, showing high separability between various sea ice types and which are invariant to the non-circularity property of the transmitted wave, are the intensity coefficients from the right-hand circular transmit and the linear horizontal receive channel and the right-hand circular on both the transmit and the receive channel, and the first parameter in the Stokes vector.

Iterative Synthetic Aperture Radar Image Registration using View Synthesis (IIRVS)

Image registration is a preprocessing operation in several synthetic aperture radar (SAR) image applications. View synthesis approach is incorporated in the standard pipeline of feature based image registration, to feed feature detector with additional synthetic views of an image. Incorporating view synthesis improves the registration performance albeit at the cost of additional memory and time to be spent on generation of views and feature extraction across all the views. Hence an iterative approach is proposed which gradually increases the views to be generated till the images are registered. The evaluation results show that the proposed approach achieves high-precision and robust registration of look-angle varied TerraSAR-X images.

Evidence of short internal waves trailing strong internal solitary waves in the northern South China Sea from synthetic aperture radar observations

Sea surface signatures of short internal waves trailing strong internal solitary waves (ISWs) have been detected on several synthetic aperture radar (SAR) images acquired by the Advanced Synthetic Aperture Radar (ASAR) onboard the European Envisat satellite over the northern South China Sea (SCS). Such configurations were found recently by Vlasenko et al. (2010) in numerical simulations carried out with the MIT general circulation model (MITgcm). They showed that the short internal waves, which have wavelengths of 1.5km and amplitudes of 20m, ride on second mode ISWs. The existence of these short internal waves, which follow a first mode ISW, can be explained in terms of the Taylor–Goldstein equation that includes a shear in the background current associated with a second mode ISW. The simulations predict that the short internal waves occur in two distinct areas, one close to the Luzon Strait (LS) and the other further west. In the first area, they are generated by the disintegration of a baroclinic bore, which is generated by the interaction of the tidal current with the steep two-ridged topography in the LS. In the second area, they are generated when the faster first mode ISW overtakes the second mode ISW of the previous tidal cycle. We have screened the ASAR archive of the European Space Agency (ESA) and found many SAR images acquired over the northern SCS showing sea surface signatures of such short internal waves trailing a much longer first mode strong ISW. The detailed analysis of six of these SAR images shows good correlation between modeled and observed internal wave fields.

An overview of small satellites in remote sensing*

This article gives a global overview of some aspects of small satellite developments since the launch of Sputnik‐1 50 years ago. These developments are offering new opportunities for remote sensing. *. Based on a paper presented at the International Workshop on Earth Observation Small Satellites for Remote Sensing Applications, Kuala Lumpur, Malaysia, 20–23 November 2007. The earliest satellites were small but, as time went on, the satellites that were flown were developed to serve several different projects and they became larger and more expensive and took a long time to design, build and be launched. One of the extreme examples was Envisat. For these large satellites compromises often had to be made between different objectives and different instruments. A failure of the whole system meant the death of many different projects. The future is likely to see more small satellites, each of which is dedicated to a particular mission objective and carries a single instrument. Through this approach more and more countries around the world are becoming involved in Earth observation from space, not just in using the data from the major established systems but also in constructing their own systems. There were some small, low‐cost satellites in the early days, but they were overlooked or considered toys by the space community. The first microsatellites were built by enthusiasts of the amateur radio community and launched in the early 1960s. The invention/introduction of the microprocessor in the 1970s represented a quantum jump for the onboard capabilities of a spacecraft. This technology introduction represented a prime catalyst in the development of microsatellites since it enabled small physical structures in support of sophisticated data handling applications. The engineering of microsatellites, which emerged in the early 1980s, took a radical change of approach from the custom design of traditional spacecraft, namely a design‐to‐capability scheme to achieve cost reductions by focusing on available, and existing technologies using a general purpose bus and ‘off‐the‐shelf’ components and instruments. The new approach of small satellite design was pioneered by Surrey Satellite Technology Ltd (SSTL) of Surrey University, UK. SSTL's lead has now been followed by various companies and space agencies throughout the world. A key feature of this work is the development of microsatellite technology transfer programmes, providing partnerships and on‐the‐job training of engineers and scientists of foreign national organizations in cooperative programmes – in particular to those who were not in a position to start or afford their own space projects – to participate in the development of their own microsatellites. In addition to discussing these developments, this article also covers small satellite classification, small satellite initiatives in the USA, small satellite development in the rest of the world, some aspects of the technology and applications of small satellites, and small satellites developed by universities, particularly the CubeSats programme. Today, small satellites are changing the economics of space. These spacecraft embrace cutting edge Commercial Off‐The‐Shelf (COTS) technology, permitting novel and less‐expensive ways to perform meaningful observation missions, although there are various technical challenges. There are several synthetic aperture radar (SAR) and hyperspectral imaging missions on small satellites in operation and in planning.

Estimation of the thin ice thickness and heat flux for the Chukchi Sea Alaskan coast polynya from Special Sensor Microwave/Imager data, 1990–2001

One of the largest Arctic polynyas occurs along the Alaskan coast of the Chukchi Sea between Cape Lisburne and Point Barrow. For this polynya, a new thin ice thickness algorithm is described that uses the ratio of the vertically and horizontally polarized Special Sensor Microwave/Imager (SSM/I) 37‐GHz channels to retrieve the distribution of thicknesses and heat fluxes at a 25‐km resolution. Comparison with clear‐sky advanced very high resolution radiometer data shows that the SSM/I thicknesses and heat fluxes are valid for ice thicknesses less than 10–20 cm, and comparison with several synthetic aperture radar (SAR) images shows that the 10‐cm ice SSM/I ice thickness contour approximately follows the SAR polynya edge. For the twelve winters of 1990–2001, the ice thicknesses and heat fluxes within the polynya are estimated from daily SSM/I data, then compared with field data and with estimates from other investigations. The results show the following: First, our calculated heat losses are consistent with 2 years of over‐winter salinity and temperature field data. Second, comparison with other numerical and satellite estimates of the ice production shows that although our ice production per unit area is smaller, our polynya areas are larger, so that our ice production estimates are of the same order. Because our salinity forcing occurs over a larger area than in the other models, the oceanic response associated with our forcing will be modified.

FOPEN SAR imaging using UWB step-frequency and random noise waveforms

The detection and identification of targets obscured by foliage have been topics of great interest. Several synthetic aperture radar (SAR) experiments have demonstrated promising images of terrain and man-made objects obscured by dense foliage, by using either linear frequency modulation (LFM) or step-frequency waveforms. We present here the methodology and results of a comparative study on foliage penetration (FOPEN) SAR imaging using ultrawideband (UWB) step-frequency and random noise waveforms. A statistical-physical foliage transmission model is developed for simulation applications. The foliage obscuring pattern is analyzed by means of the technique of paired echoes. The results of the comparative study demonstrates the ability of a UHF band UWB random noise radar to be used as a FOPEN SAR. Advantages of the random noise radar system include covert detection and immunity to radio frequency interference (RFI).

Unsupervised estimation of speckle noise in radar images

AbstractSpeckle in radar images has the characteristic of a multiplicative noise. In this article, two unsupervised methods are introduced to estimate the speckle noise statistics using the mean and the standard deviation of small image blocks (4 × 4, or 6 × 6 pixels). Since most radar images contain many small homogeneous areas, a scatter plot of the standard deviation versus the mean can reveal the characteristic of the noise. The blocks from inhomogeneous areas have higher values for the standard deviation, and they are scattered above the main cluster. They are considered as outliers, and should be excluded in the statistical estimation. These two methods are designed for obtaining a linear fit in the scatter plot by ignoring outliers. Several synthetic aperture radar(SAR) images are used for illustration.