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Polarimetric radar provides useful information on scattering mechanisms, and advances in polarimetric synthetic aperture radar (POLSAR) technology have shown the effect of polarization information on various applications. The disadvantage of POLSAR is low azimuth resolution capability. Since the effective pulse repetition frequency (PRF) in each polarimetric channel of POLSAR is half the total PRF, the resolution is twice as low as the single-polarization SAR. This drawback may be mitigated by employing a superresolution method designed for polarimetric radar such as polarimetric bandwidth extrapolation (PBWE), previously proposed by the authors. Thus far, the authors only empirically showed that polarization information helps in improving resolution via numerical simulations. In this paper, theoretical analysis on the resolution of a polarimetric radar is provided. Along with the resolution, estimation accuracy of the polarization property of the target is studied. In the analysis, we employ the recently proposed metric called the statistical resolution limit (SRL) that provides the highest resolution achievable by any unbiased parametric spectral estimator. The SRL of polarimetric radar is derived and compared with that of single-polarization radar. The Cramer-Rao bound (CRB) of the polarization estimation error of the polarimetric radar is also derived. The complexified full Fisher information matrix and the CRBs of signal parameters are derived first for the general multichannel signal in nonwhite Gaussian noise. Then, the SRL and the polarization estimation error are derived using the CRBs of signal parameters for the cases where two point targets are closely located. It is shown analytically and numerically that the polarization information helps in improving the SRL. It is also shown that the polarimetric processing significantly improves the accuracy of the polarization estimation when two targets are located closer than the Fourier resolution cell. Finally, the performance of the PBWE is evaluated via simulations and is compared to the SRL and the CRB for the polarization estimation.

Synthetic Aperture Radar (SAR) can take a fine radar image without relation to sunshine condition. Recently, video generated from SAR is discussed. The radar video offers the practical understanding of the target motion without the added implement. The radar video is often generated from raw data in spotlight mode. In contrast, we propose the radar video generated from SAR image. The proposed scheme provides a low complexity and the freedom of the observation mode. In the paper, we show the process of the proposed scheme and indicate the snapshot image of radar video made of our air-borne stripmap SAR data or Advanced Land Observing Satellite-2 data. The images show possibility of the radar video with stripmap mode or space-borne SAR.

Inverse synthetic aperture radar (ISAR) is one of the radar techniques used to observe 2-D images of a remotely based target using radio waves. If we keep observing the target and consecutively generate multiple ISAR images, which we call an ISAR movie, the target image varies considerably due to the motion of the target. The authors have proposed an algorithm for reconstructing a 3-D target shape from an ISAR movie; however, the algorithm requires a priori knowledge of the relative motion of the target. In this paper, we propose a novel method that estimates the relative motion and the 3-D shape of the target using a multistatic ISAR movie.

For urban area monitoring, detection and classification of small targets with synthetic aperture radar imagery are one of the useful solutions. The conventional method has the problem that when a target on both master and slave images at the same position has the same radar cross section, it does not classify the target as either a slightly moved reparked vehicle or as a different vehicle. To overcome this problem, we propose a Fourier-transform-based simple phase compensation method for both accurate coherence estimation and classification of the reparked vehicle's status. The proposed method obtains the maximum value of the frequency basis, and also determines the threshold, which is based on effective sample number, with a constant false alarm rate. This number is determined by the peak signal-to-noise ratio in estimation window, and are used on the preprocessed probability density function for each sample number. Finally, the proposed method classifies a target as either a slightly moved vehicle or as a different vehicle by using both the proposed coherence and threshold detection, which enables it to determine the target status. Experimental results with the COSMO-SkyMed X-band spotlight SAR images demonstrate the effectiveness of the proposed method.

When vehicles and ships are observed by radar, echoes from the target are buried in the echoes (clutter) from the ground and the sea surface in the background and detection becomes difficult. Previously, a method known as a Polarimetric Whitening Filter (PWF) was proposed as a target detection technique that focuses on the difference in the polarizations of the clutter and the target and verified its effectiveness. In addition, the authors proposed the Polarimetric Notch Filter (PNF) as a clutter suppression scheme in an environment with a low signal-to-clutter power ratio (SCR) and verified the achievement of superior improvement in the SCR performance. In this paper, we propose a target detection algorithm that obtains a constant probability of false alarm by whitening the polarization characteristic of the residual clutter power after suppressing the clutter power by the PNF. From the results of evaluations by computer simulation, we see that the SCR improvement factor of the proposed method was on average about 1.5 dB better than conventional PWF, but the target detection probability was nearly identical. In addition, the results of the performance evaluation of the polarization data of the noise of asphalt and vehicles acquired by polarimetric FMCW radar in the 95-GHz band where the SCR improvement factors of PNF and PWF were 7.44 and 5.85 dB, respectively, and the SCR improvement factor of PNF was 1.59 dB better. Although the target detection probability was somewhat higher for PNF than PWF, they were nearly identical. © 2004 Wiley Periodicals, Inc. Electron Comm Jpn Pt 1, 88(3): 33–43, 2005; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecja.20158

The remote sensing Synthetic using Aperture Radar can obtain the information of moving targets on the earth surface using MTI (Moving Target Indication) technique, which detects differentiation of the surface image data obtained in successive sessions taken with two antennas mounted on one satellite or two satellites flying in a close formation. In the latter case, the operation of the differentiation is usually performed at the ground station, then each satellite needs to transmit the large amount of data to the ground station separately, which requires broad downlink bandwidths. However, the earth surface image data at the two satellites clearly have a strong correlation since the static background image data other than the moving targets are essentially the same except for some noise factors. Focusing on this fact, we claim that the transmission data can and should be reduced by taking off the redundancy of the two data and sending only the differential parts. In this paper, we discuss the coding theory matter related to this redundancy suppression first, and then discuss source, channel and network coding, and also the Slepian-Wolf theorem for two correlated sources. We next propose a coding and compressing scheme for a certain simplified model. We further generalize it in order to apply this idea to a more realistic model and present a procedure of the proposed scheme.

This paper presents an experimental result to demonstrate azimuth ambiguity suppression with the displaced phase center antenna technique that is promising technique to realize the high resolution wide swath imagery for spaceborne synthetic aperture radar (SAR). The dual receiver antenna data was acquired by airborne Ku-band SAR. In this paper, we propose a signal compensation procedure to cope with beam squint for the following coherent signal processing such as the dual channel reconstruction algorithm. The azimuth ambiguity suppression capability is evaluated by comparing the image reconstructed from dual-receiver channel to the single receiver channel image. The experimental result shows significant azimuth ambiguity suppression.

Statistical resolution limit (SRL) is a simple metric that provides the highest resolution achievable by any unbiased parametric spectral estimator. In this paper, the SRL of polarimetric radar is derived and compared with that of single polarization radar. The SRL is defined using the Cramer-Rao bound (CRB) of signal parameters for the cases where two point targets are closely located. It is shown analytically and numerically that the polarization information helps improving the SRL.

Synthetic Aperture Radar (SAR) often suffers from interference signal from various radio sources. In general, notch filters or band elimination filters have been utilized to eliminate such interference signal; however, if the bandwidth of the interference signal is relatively wide, the gap in the spectrum caused by the band elimination filter could significantly degrade the original image. We propose an algorithm to suppress relatively wide bandwidth interference while maintaining the image quality. In the algorithm, spatially variant interference suppression filter is generated based on the signal of interference free band, then the filter is applied to the interference contaminated image. Unlike the band elimination filter, the spatially variant interference suppression filter preserves the signal component within the interference contaminated band; therefore, the image distortion caused by the spectrum gap can be largely eliminated. The algorithm has been tested with a simulated interference contaminated image generated from the real 10cm resolution airborne Ku band SAR image and a TerraSAR-X image. It has been shown that while conventional band elimination filter would degrade the image quality, the image quality of the interference suppressed image obtained by the proposed algorithm is satisfactory.

Inverse synthetic aperture radar (ISAR) is one of the radar techniques used to observe two-dimensional images of a remotely based target using radio waves. If we keep observing the target and consecutively generate multiple ISAR images, which we call ISAR movie, the target image varies considerably due to the motion of the target. The authors have proposed an algorithm for reconstructing three dimensional target shape from an ISAR movie; however, the algorithm requires a priori knowledge of the relative motion of the target. In this paper, we propose a novel method that estimates the relative motion and the three dimensional shape of the target using multistatic ISAR movie.

Resolution of a radar is limited in range by its bandwidth. One of the various super-resolution techniques for improving its resolution is bandwidth extrapolation (BWE). In the technique, a linear prediction model is fitted to the data, and the model is used to extrapolate the bandwidth. In this paper, the concept of BWE is extended, and a new algorithm called polarimetric bandwidth extrapolation (PBWE) applicable to polarimetric radar data is proposed. It is shown through numerical simulations that utilization of full polarization information allows PBWE to improve the resolution beyond the conventional BWE method. Some results of physical simulation experiment using a W-band polarimetric FMCW radar and corner reflectors are shown to confirm the advantage of PBWE.