In this paper, we propose a received signal interpolation method for enhancing the performance of multiple signal classification (MUSIC) algorithm. In general, the performance of the conventional MUSIC algorithm is very sensitive to signal-to-noise ratio (SNR) of the received signal. When array elements receive the signals with nonuniform SNR values, the resolution performance is degraded compared to elements receiving the signals with uniform SNR values. Hence, we propose a signal calibration technique for improving the resolution of the algorithm. First, based on original signals, rough direction of arrival (DOA) estimation is conducted. In this stage, using frequency-domain received signals, SNR values of each antenna element in the array are estimated. Then, a deteriorated element that has a relatively lower SNR value than those of the other elements is selected by our proposed scheme. Next, the received signal of the selected element is spatially interpolated based on the signals received from the neighboring elements and the DOA information extracted from the rough estimation. Finally, fine DOA estimation is performed again with the calibrated signal. Simulation results show that the angular resolution of the proposed method is better than that of the conventional MUSIC algorithm. Also, we apply the proposed scheme to actual data measured in the testing ground, and it gives us more enhanced DOA estimation result.

We propose a novel propagation measurement scheme for terrestrial TV signal indoor reception based on a virtual array technique. The system proposed in this paper carries out two-branch recording of target signals and the reference signal. By using the signal phase reference in the reference signal, we clarify the spatial propagation characteristics obtained from the two-dimensional virtual array outputs. Outdoor measurements were performed first to investigate the validity of the proposed measurement system. The results confirm its effectiveness in accurately determining the direction-of-arrival (DOA). We then investigated the propagation characteristics in an indoor environment. The angular spectrum obtained showed clear wave propagation structure. Thus, our proposed system is promising as a very accurate measurement tool for indoor propagation analysis.

Inter-vehicle communication (IVC) system using 700 MHz band to prevent car crashes has been proposed recently. In this paper, we first apply the FDTD method to the analyses of propagation characteristics at an intersection for IVC. We investigate the propagation characteristics considering the electrical conductivities, thickness and windows of building wall and pedestrians. As a result, it is shown that the electrical conductivities and thickness of building wall have a slight influence. In contrast, windows and pedestrians have a great influence on the propagation characteristics. Furthermore, the azimuth delay profiles are obtained by using the MUSIC algorithm.

Recently, it has become important to rapidly detect human subjects buried under collapsed houses, rubble and soil due to earthquakes and avalanches to reduce the casualties in a disaster. Such detection systems have already been developed as one kind of microwave displacement sensors that are based on phase difference generated by the motion of the subject's breast. Because almost all the systems consist of single transmitter and receiver pair, it is difficult to rapidly scan a wide area. In this paper, we propose a single-frequency multistatic radar system to detect breathing human subjects which exist in the area surrounded by the transmitting and receiving array. The vibrating targets can be localized by the MUSIC algorithm with the complex amplitude in the Doppler frequency. This algorithm is validated by the simulated signals synthesized with a rigorous solution of a dielectric spherical target model. We show experimental 3D localization results using a developed multistatic Doppler radar system around 250 MHz.

An estimation method of source location of undesired electromagnetic wave from electronic devices by using the MUSIC algorithm is proposed. The MUSIC algorithm can estimate the direction of arrival accurately, however, the estimation error is large in the case of short range multiple coherent sources. In order to overcome this problem, a method to improve the estimation accuracy is presented. Experimental results show that the proposed method can reduce the maximum estimation error from 7 cm of the conventional method to 2 cm.

This paper presents a novel algorithm for spectral subtraction (SS). The method is derived from a relation between the spectrum obtained by the discrete Fourier transform (DFT) and that by a subspace decomposition method. By using the relation, it is shown that a noise reduction algorithm based on subspace decomposition is led to an SS method in which noise components in an observed signal are eliminated by subtracting variance of noise process in the frequency domain. Moreover, it is shown that the method can significantly reduce computational complexity in comparison with the method based on the standard subspace decomposition. In a similar manner to the conventional SS methods, our method also exploits the variance of noise process estimated from a preceding segment where speech is absent, whereas the noise is present. In order to more reliably detect such non-speech segments, a novel robust voice activity detector (VAD) is then proposed. The VAD utilizes the spread of eigenvalues of an autocorrelation matrix corresponding to the observed signal. Simulation results show that the proposed method yields an improved enhancement quality in comparison with the conventional SS based schemes.

This paper proposes a 2.6 GHz low cost DBF array antenna system and reports its evaluation based on our experimental results. The proposed system is partially constructed by digital devices for the simplification of hardware, and employs some techniques for improving the resolution. The system is evaluated through the DOA estimation by the MUSIC algorithm inside a radio anechoic chamber. As a result, we found that the proposed system estimates the DOA with the highest accuracy at which MUSIC algorithm can perform. Moreover, this paper discusses the estimation errors. We also found that the estimation error is particularly affected from the inaccurate element interval.

In high-speed TDMA mobile communications, frequency-selective fading is a serious problem because a delay time difference between multipath signals is large in comparison with symbol duration. We have proposed a spatial-domain RAKE receiver using a multibeam adaptive antenna to reduce frequency-selective fading and to realize path-diversity. The multibeam adaptive antenna resolves multipath signals in the spatial domain, and combines array outputs. In this paper, we propose the application of MUSIC algorithm to estimation of the time delays of multipath signals to make the incident signals coincide with a common reference signal. Because the MUSIC algorithm can estimate the time delays accurately, the BER performance of the proposed scheme is improved. Furthermore, we propose weighting factors which easily realize the maximal-ratio combining.

This paper describes a new Artificial Neural Network (ANN), UNItary Decomposition ANN (UNIDANN), which can perform the unitary eigendecomposition of the synaptic weight matrix. It is shown both analytically and quantitatively that if the synaptic weight matrix is Hermitian positive definite, the neural output, based on the proposed dynamic equation, will converge to the principal eigenvectors of the synaptic weight matrix. Compared with previous works, the UNIDANN possesses several advantageous features such as low computation time and no synchronization problem due to the underlying analog circuit structure, faster convergence speed, accurate final results, and numerical stability. Some simulations with a particular emphasis on the applications to high resolution bearing estimation problems are also furnished to justify the proposed ANN.

Recently , a short range millimeter wave or a microwave sensing system has been extensively studied to estimate a target position or a source location. It can be applied to indoor propagation analysis, carborne applications, etc. The application of the superresolution technique has been proposed to obtain a high resolution performance in the time domain or the spatial domain. However, the availability of the polarization synthesis in the receiving antennas has not been considered. In this paper, we use a pair of polarized swept frequency data and propose two modifications of the MUSIC algorithm to enhance the resolution of time delay. One modification is the correlation matrix formulation which relates to the total signal power, and the other is a polarization filtering applied to the correlation matrix. These modifications have advantages such that. 1)Reduction of the estimation problem to the delay time estimation only; 2)Easy implementation. Experimental results are illustrated to show the availability of the methods, and to confirm the high resolution performance compared with the conventional method.

A new superresolution technique is proposed for high-resolution estimation of the scattering analysis. For complicated multipath propagation environment, it is not enough to estimate only the delay-times of the signals. Some other information should be required to identify the signal path. The proposed method can estimate the frequency characteristic of each signal in addition to its delay-time. One method called modified (Root) MUSIC algorithm is known as a technique that can treat both of the parameters (frequency characteristic and delay-time). However, the method is based on some approximations in the signal decorrelation, that sometimes make problems. Therefore, further modification should be needed to apply the method to the complicated scattering analysis. In this paper, we propose to apply a time-domain null filtering scheme to reduce some of the dominant signal components. It can be shown by a simple experiment that the new technique can enhance estimation accuracy of the frequency characteristic in the Root-MUSIC algorithm.

Signal processing antennas have been studied not only for interference suppression but also for high-resolution estimation of radio environment such as directions-of-arrival of incident signals. These two applications are based on the common technique, that is, null steering. This tutorial paper reviews the MUSIC algorithm which is one of the typical high-resolution techniques. Examining the eigenvector beam patterns, we demonstrate that the high-resolution capability is realized by steering nulls. The considerations will be useful for understanding the high-resolution techniques in the signal processing antennas. We then describe a modified version of MUSIC (Root MUSIC). We show the performance and robustness of the method. Furthermore, we introduce radar target identification and two-dimensional radar target imaging. These study fields are new applications of the signal processing antennas, to which a great deal of attention has been devoted recently.

Analyzing multipath propagation structure is important to develop anti-fading techniques for high-speed digital radio systems. Several techniques have been employed to measure delay profiles and/or arrival angles. This paper presents a simultaneous estimation method of delay times and arrival angles of indoor multipath waves. We obtain frequency-domain data at different receiving antenna positions using a network analyzer. We estimate the propagation parameters by means of a two-dimensional MUSIC algorithm. In order to obtain reliable results, a two-dimensional discrete inverse Fourier transform and a gating technique are employed before the MUSIC algorithm. Simulation and experimental results show that the proposed method can estimate the propagation parameters properly.

A new superresolution technique is proposed for antenna pattern measurements. Unwanted reflected signals often impinge on the antenna when we measure it outdoors. A time-domain superresolution technique (a MUSIC algorithm) has been proposed to eliminate the unwanted signal for a narrow pass-band antenna. The MUSIC algorithm needs many snapshots to obtain a correlation matrix. This is not preferable for antenna pattern measurements because it takes a long time to obtain the data. In this paper, we propose to reduce a noise component (stochastic quantity) using the FFT and gating techniques before we apply the MUSIC. The new technique needs a few snapshots and saves the measurement time.

A superresolution technique is considered for use in antenna gain measurements. A modification of the MUSIC algorithm is employed to resolve incident signals separately in the time domain. The modification involves preprocessing the received data using a spatial scheme prior to applying the MUSIC algorithm. Interference rejection in the antenna measurements using the fast Fourier transform (FFT) based techniques have been realized by a recently developed vector network analyzer, and its availability has been reported in the literature. However, response resolution in the time domain of these conventional techniques is limited by the antenna bandwidth. The MUSIC algorithm has the advantage of being able to eliminate unwanted responses when performing antenna measurements in situations where the antenna band-width is too narrow to support FFT based techniques. In this paper, experimental results of antenna gain measurements in a multipath environment show the accuracy and resolving power of this technique.