Low-frequency Synthetic Aperture Radar Research Articles

Filtering approaches for interference suppression in low-frequency SAR

Low-frequency synthetic aperture radar (SAR) systems are of interest primarily because of their ability to see through foliage for a variety of purposes. Unfortunately, the very high frequency/ultra-high frequency bands are used by a large number of services such as television, radio and communications. The authors describe a number of different radio frequency interference suppression techniques that have been investigated and that were tested on wide bandwidth low-frequency SAR data collected on board a helicopter using the Airborne Data Acquisition System (ADAS) low-frequency radar. The least-mean-square (LMS) filter and the Wiener filter are both investigated in detail. The adaptive Wiener filter is found to have superior suppression and sidelobe performance and is also computationally much faster than the LMS filter when applied to the ADAS data.

Extended wavenumber-domain synthetic aperture radar focusing with integrated motion compensation

Modern synthetic aperture radar (SAR) systems are continually developing in the direction of higher spatial resolution. This requires the usage of high range bandwidths combined with long azimuth integration intervals. High-quality SAR processing methods, which are able to deal with such sensor parameters, are necessary for focusing the raw data of such sensors. Wavenumber-domain (ω–k) processing is commonly accepted as the ideal solution to the SAR focusing problem. However, it is only applicable to spaceborne SAR data where a straight sensor trajectory is given. In the case of airborne data, wavenumber-domain processing is limited because of its inability to perform high-precision motion compensation. Here, the extended chirp scaling (ECS) algorithm has proven to be very powerful, although it has certain limitations concerning long aperture syntheses and highly squinted geometries. In the paper, a new stripmap SAR data-processing algorithm, called extended ω–k (EOK), is analytically derived. The EOK algorithm aims to combine the high focusing accuracy of the wavenumber-domain algorithm with the high-precision motion compensation of the ECS algorithm. The new EOK algorithm integrates a three-step motion compensation correction in the general formulation of the wavenumber-domain algorithm, leading to a new airborne SAR processing scheme, which is also very robust in the cases of long synthetic apertures and high squint angles. As demonstrated, it offers the possibility of processing wide-band, low-frequency airborne SAR data up to near-wavelength resolution. The performance and accuracy of the new EOK SAR data-processing algorithm are demonstrated using simulated data in different data collection scenarios and geometries as well as using interferometric data acquired by the airborne experimental SAR system of DLR at L-band (Horn, 1996; Scheiber, 1999).

Low VHF-band backscatter from coniferous forests on sloping terrain

Low-frequency synthetic aperture radar (SAR) is a promising technique for stem volume retrieval, particularly for dense forests, due to the good penetration of forest canopies. However, it is well known that the dominant scattering mechanism, the trunk-ground dihedral interaction, decreases rapidly on sloping terrain. In this paper, we use low VHF-band SAR data, collected with CARABAS over dense coniferous forests in Sweden, to examine the effect of topography. Using flight passes with different headings, the effect of slope and aspect angle on backscatter is characterized. For tall trees (/spl sim/30 m), on the steepest slopes in the test-site (up to /spl sim/12/spl deg/), differences of up to 8 dB are observed between images acquired with different look directions relative to the slope. A physical model is developed to investigate the different scattering mechanisms and their sensitivity to terrain slopes. The model shows that the trunk-ground scattering still dominates the response for large trees on moderate slopes, and a semiempirical model for the effect of topography on backscatter is proposed. The model shows good agreement with measurements, indicating the possibility of using it to compensate for the effects of sloping terrain when retrieving stem volume in coniferous forest.

Change detection for low-frequency SAR ground surveillance

Change detection using ultra-wideband synthetic aperture radar (SAR) images in the low end of the VHF band is shown to provide excellent performance for detection of vehicle-sized objects in forest concealment. Two different change detection algorithms are discussed and their performance evaluated. The two algorithms are based on similar statistical hypothesis testing, but differ in that one operates on complex (coherent change detection) whereas the other uses magnitude (incoherent change detection) image data. Algorithm evaluation is performed using radar data acquired with the airborne CARABAS-II SAR in northern Sweden. The data were collected during a change detection experiment with concealed vehicles in boreal forests (stand volume ca. 100 m3/ha). Results show that coherent change detection gives slightly better performance using full spatial resolution of the images, whereas the incoherent change detection gives better performance when spatial averaging (2×2 resolution cells) is included. A comparison with detecting vehicles using only single-pass images shows an increase of false alarms of one to two orders of magnitude at the same probability of detection.