UWB (Ultra Wideband) radar offers great promise for advanced near field sensors due to its high range resolution. In particular, it is suitable for rescue or resource exploration robots, which need to identify a target in low visibility or acoustically harsh environments. Recently, radar algorithms that actively coordinate multiple scattered components have been developed to enhance the imaging range beyond what can be achieved by synthesizing a single scattered component. Although we previously developed an accurate algorithm for imaging shadow regions with low computational complexity using derivatives of observed ranges for double scattered signals, the algorithm yields inaccurate images under the severe interference situations that occur with complex-shaped or multiple objects or in noisy environments. This is because small range fluctuations arising from interference or random noises can produce non-negligible image degradation owing to inaccuracy in the range derivative calculation. As a solution to this difficulty, this paper proposes a novel imaging algorithm that does not use the range derivatives of doubly scattered signals, and instead extracts a feature of expansive distributions of the observed ranges, using a unique property inherent to the doubly scattering mechanism. Numerical simulation examples of complex-shaped or multiple targets are presented to demonstrate the distinct advantage of the proposed algorithm which creates more accurate images even for complicated objects or in noisy situations.

Ultra-wide band (UWB) pulse radar has high range resolution, and is thus applicable to imaging sensors for a household robot. To enhance the imaging region of UWB radar, especially for multiple objects with complex shapes, an imaging algorithm based on aperture synthesis for multiple scattered waves has been proposed. However, this algorithm has difficulty realizing in real-time processing because its computation time is long. To overcome this difficulty, this letter proposes a fast accurate algorithm for shadow region imaging by incorporating the Range Points Migration (RPM) algorithm. The results of the numerical simulation show that, while the proposed algorithm affects the performance of the shadow region imaging slightly, it does not cause significant accuracy degradation and significantly decreases the computation time by a factor of 100 compared to the conventional algorithm.

UWB (Ultra Wide-Band) pulse radar is promising for surveillance systems because it has an outstanding high range-resolution. To realize an accurate UWB radar imaging system, we propose a new approach that employs multipath echoes from a target in an indoor environment. Using multipath echoes, the proposed system can accurately estimate images, even for targets in a shadow region where the targets are out of sight of the antenna. We apply a simple interferometry technique using the multiple mirror image antennas generated by multipath propagation. We find that this simple method also produces many undesired false image points. To tackle this issue, we also propose an effective false image reduction algorithm to obtain a clear image. Numerical simulations verify that most of the false image points are removed and the target shape is accurately estimated.

The applicability in harsh optical environments, such as dark smog, or strong backlight of ultra-wide band (UWB) pulse radar has a definite advantage over optical ranging techniques. We have already proposed the extended Synthetic Aperture Radar (SAR) algorithm employing double scattered waves, which aimed at enhancing the reconstructible region of the target boundary including shadow region. However, it still suffers from the shadow area for the target that has a sharp inclination or deep concave boundary, because it assumes a mono-static model, whose real aperture size is, in general, small. To resolve this issue, this study proposes an extension algorithm of the double scattered SAR based on a multi-static configuration. While this extension is quite simple, the effectiveness of the proposed method is nontrivial with regard to the expansion of the imaging range. The results from numerical simulations verify that our method significantly enhances the visible range of the target surfaces without a priori knowledge of the target shapes or any preliminary observation of its surroundings.