An ultrawideband (UWB) multistatic radar system, typically composed of one transmitter and several receivers, is a promising solution for tracking intruders moving inside a surveillance area. In this paper, the Hough transform is used to find the time-of-arrival (TOA) curves of the targets in the scan versus propagation time image for impulse-radio UWB multistatic radars. In order to parametrize these curves, which associate target TOAs over scan time, a straight-line constant-velocity mobility model is assumed for the target, providing a reasonable computational complexity and data storage requirement. The performance of our approach is verified by experimental measurements for a single target scenario in an indoor environment, where a dense clutter is observed. We show that the target TOA points can be well discriminated from false alarms and associated over scan time, forming the target TOA curves. These TOA curves can be estimated with a good accuracy, even though the target is missed at some points. In practice, before applying our TOA association algorithm, we have to remove the unwanted clutter. Because the conventional empty-room method generates too many false alarms due to shadowing effects in indoor environments, we also develop a modified empty-room clutter removal technique and we show that it can considerably reduce the number of false alarms.

Target TOA association with the hough transform in UWB radars

SOBHANI, BITA;CHIANI, MARCO
2016

Abstract

An ultrawideband (UWB) multistatic radar system, typically composed of one transmitter and several receivers, is a promising solution for tracking intruders moving inside a surveillance area. In this paper, the Hough transform is used to find the time-of-arrival (TOA) curves of the targets in the scan versus propagation time image for impulse-radio UWB multistatic radars. In order to parametrize these curves, which associate target TOAs over scan time, a straight-line constant-velocity mobility model is assumed for the target, providing a reasonable computational complexity and data storage requirement. The performance of our approach is verified by experimental measurements for a single target scenario in an indoor environment, where a dense clutter is observed. We show that the target TOA points can be well discriminated from false alarms and associated over scan time, forming the target TOA curves. These TOA curves can be estimated with a good accuracy, even though the target is missed at some points. In practice, before applying our TOA association algorithm, we have to remove the unwanted clutter. Because the conventional empty-room method generates too many false alarms due to shadowing effects in indoor environments, we also develop a modified empty-room clutter removal technique and we show that it can considerably reduce the number of false alarms.
2016
Sobhani, Bita; Zwick, Thomas; Chiani, Marco
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11585/551746
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