The purpose of this study is the real-time estimation of Doppler spectral moments for precipitation in the presence of ground clutter overlap. The proposed method is a frequency domain approach that uses a Gaussian model both to remove clutter spectrum and to estimate weather spectrum. The main advantage of this method is that it does not use processes like several fitting procedures and enables to estimate profiles of precipitation in a short processing time. Therefore this method is efficient for real-time radar observation with high range and time resolution. The performance of this method is evaluated based on simulation data and the observation data acquired by the Ku-band broad band radar (BBR) [1].

The complex-valued self-organizing map (CSOM) realizes an adaptive distinction between plastic landmines and other objects in landmine visualization systems. However, when the spatial resolution in electromagnetic-wave measurement is not sufficiently high, the distinction sometimes fails. To solve this problem, in this paper, we propose two techniques to enhance the visualization ability. One is the utilization of SOM-space topology in the CSOM adaptive classification. The other is a novel feature extraction method paying attention to local correlation in the frequency domain. In experimental results, we find that these two techniques significantly improve the visualization performance. The local-correlation method contributes also to the reduction of the number of tuning parameters in the CSOM classification.

Ultra wideband (UWB) radar cross sections (RCSs) of several targets have been measured using various combinations of transmitting and receiving linear polarizations (V-V, H-H, and +45- -45) with a view to obtaining information on the design of vehicular short-range radars. This paper reports the UWB RCSs (σLR and σLL) of a typical passenger automobile using two circular polarization combinations (L and R denote left and right circular polarizations). The wideband measurements were carried out with use of a vector network analyzer by sweeping the frequency from 24.5 to 28.8 GHz in a radio anechoic chamber. The UWB RCSs were derived by integrating the received power in the frequency domain. Similar to the linear polarization results, fluctuations of the RCSs were smaller in the UWB than in narrowband for both L-R and L-L, because the ultra-wide bandwidth cancels out RCS plunges caused by narrowband interference among reflected waves from various facets of the target. The median of (σLR- σLL) was 2 dB, while the median of (σHH - σ+45 - -45) or (σVV-σ+45- -45) was 6 dB. This is because the body of the automobile comprises a number of smaller scattering objects yielding σ LL, either similar to the corner reflectors or asymmetrical to the radar boresight. Frequency-domain responses showed a number of notches caused by the interference between numerous reflecting waves having power levels of a similar order and different round-trip path lengths. Some representative reflective parts of the automobile were identified through analyses of time-domain responses.

UWB (Ultra Wide-Band) pulse radar is a promising candidate for surveillance systems designed to prevent crimes and terror-related activities. The high-speed SEABED (Shape Estimation Algorithm based on BST and Extraction of Directly scattered waves) imaging algorithm, is used in the application of UWB pulse radar in fields that require realtime operations. The SEABED algorithm assumes that omni-directional antennas are scanned to observe the scattered electric field in each location. However, for surveillance systems, antenna scanning is impractical because it restricts the setting places of the devices. In this paper, movement of a body is used to replace antenna scanning. The instantaneous velocity of any given motion is an unknown variable that changes as a function of time. A pair of antennas is used to analyze delay time to estimate the unknown motion. We propose a new algorithm to estimate the shape of a human body using data obtained from a human body passing stationary antennas.

This paper presents the near-field to far-field transformation for an outdoor radar cross section (RCS) range. Direct measurement of the large actual target requires quite a long measurement range. The near-field to far-field RCS transformation method achieves the reduction of measurement range. However the non-uniformity of the incident electric field distribution on the target causes some errors in RCS prediction. We propose a novel near-field to far-field RCS transformation method that can be applied to an outdoor RCS measurement. The non-uniformity of the incident electric field distribution is successfully resolved by introducing the correction term of the ground bounce. We investigate the validity of the proposed method by the simulation and measurement.

Pulse radars with UWB signals are promising as a high-resolution imaging technique that can be used for the non-destructive measurement of surface details in industrial products such as antennas and aircraft. We have already proposed a fast 3-D imaging algorithm, SEABED, that utilizes a reversible transform between the time delay and the target boundary. However, data acquisition is time-consuming when obtaining an accurate image because it assumes a mono-static radar with 2-D scanning of an antenna. In this paper, we utilize linear array antennas and propose a fast and accurate imaging algorithm. We extend the reversible transform for mono-static radars to apply to bi-static radars to reduce the data acquisition time. The effectiveness of the proposed method is verified with numerical simulations and experiments.

This paper presents a coherent decomposition scheme for polarimetric SAR data. Coherent decomposition means the decomposition is applied to a single or a few scattering matrix data. Based on the scattering matrix acquired with an FM-CW polarimetric SAR system, we have devised a simple decomposition technique using the coherency matrix for the purpose of identifying scatterers. This paper presents the decomposition technique and some decomposition results obtained by a fully polarimetric FM-CW radar. It is shown the scattering mechanisms are well recovered and the orientation angles of wire scatterer are precisely measured.

Spatial filtering is a useful method to suppress undesired reflection from unwanted scatters in Radar Cross Section (RCS) measurements. Actually, it is difficult to prepare an ideal field which satisfies the far-field criterion for RCS measurements of large targets. We applied the filtering method to a bistatic RCS measurement in a near field and investigated the validity of that method by varying the scanning angular span. Electromagnetic simulations show that predicted RCS profiles from near-field data with unwanted scatters closely matched far-field reference data of the test target. In conclusion, the results show that the method is effective for bistatic RCS measurements in practical field enviroments.

A C-band polarimetric radar on Okinawa Island successfully observed large-scale bird migrations over the western Pacific Ocean. The birds generated interesting polarimetric signatures. This paper describes the signatures and speculates bird behavior.

The performance of the adaptive scan for spaceborne rain radar, which uses a quick scan for rain search followed by a normal or concentrated scan only for rainy areas, are studied through a simulation using TRMM (Tropical Rainfall Measuring Mission) Precipitation Radar (PR) data. Trade-off studies are performed to find an optimum quick-scan and rain search method to minimize rain missing and false alarm of rain area. Using the optimum method thus determined, consecutive 8-day TRMM PR data are used to statistically evaluate the performance of the adaptive scan in terms of sensitivity improvement and power consumption saving. It is shown that more than 3-dB improvement in effective signal-to-noise ratio (SNe) can be achieved for 40% of the total observations. Alternatively, about 26% power saving can be achieved if the SNe is kept the same.

A variable phase shifter using a movable waffle iron metal plate comprised of iron rods a quarter-wavelength in length is proposed. A study of the waffle iron structure was carried out and the design method for creating a structure that would achieve large phase changes, small loss, and good isolation between adjacent phase shifters is discussed. Experiments on 1-port and 2-port phase shifters operating in the 5 GHz band show that they not only have low loss characteristics but also wide phase changes. Furthermore, the application to phased array antennas using the proposed phase shifter and its principle are demonstrated.

Orbit estimation of space debris, objects of no inherent value orbiting the earth, is a task that is important for avoiding collisions with spacecraft. The Kamisaibara Spaceguard Center radar system was built in 2004 as the first radar facility in Japan devoted to the observation of space debris. In order to detect the smaller debris, coherent integration is effective in improving SNR (Signal-to-Noise Ratio). However, it is difficult to apply coherent integration to real data because the motions of the targets are unknown. An effective algorithm is proposed for echo detection and orbit estimation of the faint echoes from space debris. The characteristics of the evaluation function are utilized by the algorithm. Experiments show the proposed algorithm improves SNR by 8.32 dB and enables estimation of orbital parameters accurately to allow for re-tracking with a single radar.

Classification of terrain is one of the most important applications of Polarimetric Synthetic Aperture Radar (POLSAR) image analysis. This paper presents a simple method to classify terrain by the use of the correlation coefficients in the circular polarization basis together with the total power of the scattering matrix in the X-band. The reflection symmetry condition that the co-polarized and the cross-polarized correlations are close to zero for natural distributed scatterers is utilized to extract characteristic parameters of small forests or cluster of trees, and oriented urban building blocks with respect to the direction of the radar illumination. Both of these kinds of scatterers are difficult to identify in high resolution POLSAR images of complex urban areas. The indices employed here are the correlation coefficient, a modified coefficient normalized by the reflection symmetric conditional case, and the total power. It is shown that forest areas and oriented building blocks are easily detected and identified. The terrain classification yielded by these combinations is very accurate as confirmed by photographic ground truth images.

This paper addresses the ambiguity of radar altimetry related to the statistical nature of the Earth's surface roughness. A hypothetic altimetry method, which provides a simple way to quantify the measures of ambiguity, is proposed. Cramer-Rao lower bounds on the variances of estimates for the mean altitude and root-mean-square height of the sea surface are suggested as such quantitative measures. The accuracy of some types of air- and spaceborne radar altimeters is numerically analyzed against the derived lower bounds.

This paper analyses the autocorrelation function of return waveforms in high precision radar altimeters employing chirp-pulse transmit signal under the condition of near-nadir deviations of the antenna boresight axis. It is shown that in case of ultra wideband transmit signals providing very high time resolution the correlation function can be approximated by a product of two separate functions of time.

This paper examines seasonal change of the true water area of Lake "Sakata" by using Polarimetric Synthetic Aperture Radar (POLSAR) image analysis. The true water area includes not only the body of water but also the water area under emerged-plants and/or floating-leave plants in the lake. Statistical POLSAR image analysis is carried out for both X- and L-band data, based on the three-component scattering power decomposition method, where the decomposed components are surface scattering, double-bounce scattering and volume scattering components. From the results of the image analysis for the L-band POLSAR data acquired by Pi-SAR system, it is found that strong double-bounce scattering can be observed at the vicinity of the boundary region between water area and the surrounding emerged-plants area in early and middle summer. This phenomenon is an important factor for environmental monitoring. To verify the generating mechanism of the double-bounce scattering, the Finite-Difference Time-Domain (FDTD) polarimetric scattering analysis is also executed for a simplified boundary model, which simulates the local boundary region around the lake and consists of lots of vertical thin dielectric pillars on a perfect electric conductor (PEC) plate or on a PEC and dielectric hybrid plate. Taking into account the polarimetric feature of the double-bounce scattering obtained by both the FDTD and POLSAR image analyses, one can distinguish the actual water area from the bush of the emerged-plants around the lake, even when the water area is concealed by emerged-plants and/or floating-leave plants. Consequently, it is found that by using the proposed approach, one can estimate the true water area seasonal change for the lake and the surrounding wetland.

Target shape estimation with UWB pulse radars is a promising imaging technique for household robots. We have already proposed a fast imaging algorithm, SEABED, that is based on a reversible transform BST (Boundary Scattering Transform) between the received signals and the target shape. However, the target image obtained by SEABED deteriorates in a noisy environment because it utilizes a derivative of received data. In this paper, we propose a robust imaging method with an envelope of circles. We clarify by numerical simulation that the proposed method can realize a level of robust and fast imaging that cannot be achieved by the original SEABED.

UWB pulse radars enable us to measure a target location with high range-resolution, and so are applicable for measurement systems for robots and automobile. We have already proposed a robust and fast imaging algorithm with an envelope of circles, which is suitable for these applications. In this method, we determine time delays from received signals with the matched filter for a transmitted waveform. However, scattered waveforms are different from transmitted one depending on the target shape. Therefore, the resolution of the target edges deteriorates due to these waveform distortions. In this paper, a high-resolution imaging algorithm for convex targets is proposed by iteration of the shape and waveform estimation. We show application examples with numerical simulations and experiments, and confirm its capability to detect edges of an object.

Ultra-wideband pulse radars are promising candidates for 3-dimensional environment measurements by autonomous robots. Estimating 3-dimensional target shapes by scanning with an omni-directional antenna is an ill-posed inverse problem. Conventional algorithms such as the synthetic aperture method or parametric algorithms have a problem in terms of their calculation times. We have clarified the existence of a reversible transform between received data and target shapes for 3-dimensional systems. Calculation times are remarkably reduced by applying this transform because it directly estimates target shapes without iterations. We propose a new algorithm based on the transform and present an application example using numerical simulations. We confirm that the proposed algorithm has sufficient accuracy and a short calculation time.

A feature for classification of shallowly buried landmine-like objects using a ground penetrating radar (GPR) measurement system is proposed and its performance is evaluated. The feature for classification employed here is a time interval between two pulses reflected from top and bottom sides of landmine-like objects. First, we estimate a time resolution required to detect object thickness from GPR data, and check the actual time resolution through laboratory experiment. Next, we evaluate the classification performance using Monte Carlo simulations from dataset generated by a two-dimensional finite difference time domain (FDTD) method. The results show that good classification performance is achieved even for landmine-like objects buried at shallow depths under rough ground surfaces. Furthermore, we also estimate the effects of ground surface roughness, soil inhomogeneity, and target inclination on the classification performance.