Backscatter communication is an emerging wireless access technology to realize ultra-low power terminals exploiting the modulated reflection of incident radio wave. This paper proposes a method to measure the phase angle of backscatter link using principal component analysis (PCA). The phase angle measurement of backscatter link at the receiver is essential to maximize the signal quality for subsequent demodulation and to measure the distance and the angle of arrival. The drawback of popular phase angle measurement with naive phase averaging and linear regression analysis is to produce erroneous phase angle, where the phase angle is close to $pmrac{pi}{2}$ radian and the signal quality is poor. The advantage of the proposal is quantified with a computer simulation, a conducted experiment and radio propagation experiments.

This paper proposes a method to detect buildings and houses whose walls are not parallel to Synthetic Aperture Radar (SAR) flight path. Experimental observations show that it is difficult to detect these targets because of small backscattering characteristics. The detection method is based on the correlation coefficient in the circular polarization basis, taking full advantage of Polarimetric SAR (POLSAR) data. Since the correlation coefficient is real-valued for natural distributed targets with reflection symmetry and for non-natural targets orthogonal to illumination direction, and it becomes a complex number for non-natural targets aligned not orthogonal to radar Line-Of-Sight (LOS), the value seems to be an effective index for detection of obliquely aligned non-natural targets. The detection results are shown using the X-band Polarimetric and Interferometric SAR (Pi-SAR) single-path data set in conjunction with other polarimetric indices.

An analysis method is proposed for nonstationary waveforms. Modelling of a nonstationary waveform is first given in this paper. A waveform is represented by multiple oscillations. The instantaneous phase angle of each oscillation is written by three terms, predictive component, residual component, and initial phase constant. By this modelling, waveform analysis results in estimations of frequency, calculation of residual pbase in instantaneous phase angle. The Instantaneous Maximum Entropy Methods (IMEN) is utilized for frequency estimation. The residual phase angle is obtained by the Vandermonde matrix and the condition of continuity of phase angle among n-neighbourhood. Another analysis method is also proposed by the normalization of waveform parameters. The evaluation of the proposed method is done using artificially composed waveform signals. Novel and useful knowledge was provided by this analysis.