Ultra-wideband (UWB) pulse radars have a definite advantage in high-range resolution imaging, and are suitable for short-range measurements, particularly at disaster sites or security scenes where optical sensors are rarely suitable because of dust or strong backlighting. Although we have already proposed an accurate imaging algorithm called Range Points Migration (RPM), its reconstructible area is too small to identify the shape of an object if it is far from the radar and the size of the aperture is inadequate. To resolve this problem, this paper proposes a novel image expansion method based on ellipse extrapolation; it enhances extrapolation accuracy by deriving direct estimates of the observed range points distributed in the data space. Numerical validation shows that the proposed method accurately extrapolates part of the target boundary, even if an extremely small region of the target boundary is obtained by RPM.

Pulse radars with UWB signals are promising as a high-resolution imaging technique that can be used for the non-destructive measurement of surface details in industrial products such as antennas and aircraft. We have already proposed a fast 3-D imaging algorithm, SEABED, that utilizes a reversible transform between the time delay and the target boundary. However, data acquisition is time-consuming when obtaining an accurate image because it assumes a mono-static radar with 2-D scanning of an antenna. In this paper, we utilize linear array antennas and propose a fast and accurate imaging algorithm. We extend the reversible transform for mono-static radars to apply to bi-static radars to reduce the data acquisition time. The effectiveness of the proposed method is verified with numerical simulations and experiments.

Target shape estimation with UWB pulse radars is a promising imaging technique for household robots. We have already proposed a fast imaging algorithm, SEABED, that is based on a reversible transform BST (Boundary Scattering Transform) between the received signals and the target shape. However, the target image obtained by SEABED deteriorates in a noisy environment because it utilizes a derivative of received data. In this paper, we propose a robust imaging method with an envelope of circles. We clarify by numerical simulation that the proposed method can realize a level of robust and fast imaging that cannot be achieved by the original SEABED.

UWB pulse radars enable us to measure a target location with high range-resolution, and so are applicable for measurement systems for robots and automobile. We have already proposed a robust and fast imaging algorithm with an envelope of circles, which is suitable for these applications. In this method, we determine time delays from received signals with the matched filter for a transmitted waveform. However, scattered waveforms are different from transmitted one depending on the target shape. Therefore, the resolution of the target edges deteriorates due to these waveform distortions. In this paper, a high-resolution imaging algorithm for convex targets is proposed by iteration of the shape and waveform estimation. We show application examples with numerical simulations and experiments, and confirm its capability to detect edges of an object.