Image Reconstruction by means of Kalman Filtering in Passive Millimetre- Wave Imaging

Passive millimetre-wave (PMMW) imaging detects thermal noise generated and reflected by metallic and non-metallic objects even in wet and foggy conditions. The use of a PMMW imaging system on a small unmanned aerial vehicle (UAV) offers extremely attractive possibilities for applications such as search and rescue oper-ations, but the design is severely limited by the size of the UAV. A possible solution is a long, thin antenna array fitted under the wings of the UAV. Such an antenna has a narrow beam along the plane perpendicular to the flight path, but a very broad beam along the plane of the flight path blurs the image, making it difficult to accurately determine the position of an object or to differentiate between objects situated along the plane of the flight path. This paper proposes a technique of image reconstruction based on the Kalman filter to reconstruct an accurate image of the target area from such a detected signal. It is shown that given a simulated target area, populated with an arbitrary number of objects, the Kalman filter is able to successfully restore the image using the measured antenna pattern to model the scanning process and reverse the blurring effect