Synthetic aperture radar (SAR) processing on agile radar platforms requires a very accurate estimate of position due to the unpredictable trajectory of such platforms. This is even more challenging in GPS-denied scenarios where the bias in inertial sensors cannot be compensated. In this study, we propose a 3D radar-Aided positioning method based on SAR autofocusing to achieve subresolution positioning accuracy. The proposed multibeam autofocus algorithm builds on multiple SAR motion compensation techniques to generalize and provide a framework for simultaneous omnidirectional imaging and trajectory estimation and correction while taking advantage of the beamforming capabilities of the antenna array. Our initial simulations and proof of concept show that the performance of the proposed approach is adequate even in low signal-To-noise ratio cases.

This paper investigates the benefits of multichannel processing for inverse synthetic aperture radar (ISAR) imaging. There are potential advantages of multichannel processing in radar systems, for example, improved motion estimation, clutter suppression, extraction of supporting information, such as sea wave direction and speed, and ship wake imaging. The current study focuses on two multichannel techniques, namely the oceanic displaced phase centre antenna (ODPCA) and the minimum variance distortionless response (MVDR) techniques, to suppress (ambiguous) clutter and enhance focused target responses even in the proximity of other target responses. These techniques are validated using experimental multichannel radar data from an airborne measurement campaign in a maritime environment.

Continuous navigation is crucial for small drones when flying a pre-planned route or during autonomous flight. In scenarios where a global positioning system (GPS) signal is unavailable, drift in the onboard sensors causes the inertial navigation system (INS) to quickly deviate from the planned route. This paper proposes a radar-aided navigation method for small drones which is able to estimate the horizontal velocity and height of the platform independently from GPS. The method is based on an omnidirectional radar system and takes advantage of multi-look processing to increase estimation precision. Simulations and experiments verify that an omnidirectional radar can be used to successfully estimate the velocity and course of a small drone platform.

In this paper, a wire detection algorithm is proposed for synthetic aperture radar (SAR) images. The algorithm is specifically designed for SAR images generated from an agile, drone-mounted, omnidirectional radar array to be used for the detection of improvised explosive devices (IEDs). A multistage approach consisting of denoising, constant false alarm rate (CFAR) thresholding, feature extraction, and automated detection using the Radon transform, is proposed and applied to a set of SAR images with multiple aspect angles. At each detection step, the look-angles of individual pixels are used to remove false alarms, and improve detection accuracy. The algorithm is tested using measured data and provides an acceptable detection performance on straight wire segments even in the presence of a strong background clutter.

The Aswan High Dam, Egypt, was built in the 1960s and is one of the biggest dams in the world. It stopped the seasonal flood of Nile river allowing the urban expansion of cities/villages and the full year cultivation, producing 10×10 9 kWh of power annually. The dam is located in an area where several earthquakes (M L <;6) occurred from 1981 to 2007. In this paper, we want to identify any potential damage that could be caused to the dam, and assess its overall structural stability using Multi-Temporal InSAR (MT-InSAR). To reach this goal, we process Envisat data from descending orbits acquired between 2003 and 2010. Our initial estimates show relatively small rates (maximum around -3 mm/yr in the satellite Line-Of-Sight) of subsidence, whose implications must be further investigated. In addition, we perform a preliminary stress-strain analysis of the dam using FEL and FEM methods to assess if the detected movements correspond to the expected vertical behavior for such mega-structure.

Part of Session 3 - Sentinel-1 TOPS InSAR results