In order to generate linear polarization images we use the PMMW quasi-optical imaging system, mentioned in Section 3, with a single linear polarization characteristic.
In this paper, all raw images are obtained by PMMW quasi-optical imaging system with the condition that the object distance, 50, between an object and the lens is 2500 mm and the image distance, 51, from the lens to the receiver through the metal reflector is about 500 mm.
The polarization-dependent PMMW images of a metal sphere, which is usually used as a standard target for microwave remote sensing applications, are measured by the developed quasi-optical imaging system while varying the receiver polarization angle with the rotation step of [pi]/8.
As shown in Figure 10(a), the measured PMMW images of the metal sphere show that a PMMW single polarization image has fewer pixel numbers than the expected values indoors making it difficult to recognize an object.
Figure 13 displays the PMMW raw images of the metal and ceramic cups through the receiver polarization angle.
The linear polarization sum imaging is proposed to improve the PMMW image quality for target recognition indoors.
When a PMMW sensor looks at the terrain, sky or a metal object, the directly measurable parameter is the antenna temperature.
h] can be measured as the ratio of antenna temperature differences, even though its value is independent of the antenna temperatures that describe the PMMW scenario.
Use of these linear relationships leads immediately to the PMMW diagram shown in Figure 4.
Several PMMW scenario predictions are easily visualized with the aid of the PMMW diagram.
The linear nature of object and terrain antenna temperature relationships provides graphical support for the prediction that relative contrast temperatures within the PMMW scenario are independent of sky noise temperature, as are the values of Ch and eg.
Terrain clutter seen by a PMMW sensor is not a source of noise.