This paper presents two types of two-dimensional (2-D) adaptive beamforming algorithm which have high rate of convergence. One is a linearly constrained minimum variance (LCMV) beamforming algorithm which minimizes the average output power of a beamformer, and the other is a generalized sidelobe canceler (GSC) algorithm which generalizes the notion of a linear constraint by using the multiple linear constraints. In both algorithms, we apply a 2-D lattice filter to an adaptive filtering since the 2-D lattice filter provides excellent properties compared to a transversal filter. In order to evaluate the validity of the algorithm, we perform computer simulations. The experimental results show that the algorithm can reject interference signals while maintaining the direction of desired signal, and can improve convergent performance.

An adaptive infinite impulse response (IIR) filter implemented using an allpass and a minimum phase system has an advantage of its poles converging to the poles of the unknown system when the input is a white signal. However, when the input signal is colored, convergence speed deteriorates considerably, even to the point of lack of convergence for certain colored signals. Furthermore with a colored input signal, there is no guarantee that the poles of the adaptive digital filter (ADF) will converge to the poles of the unknown system. In this paper we propose a method which uses a linear predictor filter to whiten the input signal so as to improve the convergence characteristic. Computer simulation results confirm the increase in convergence speed and the convergence of the poles of the ADF to the poles of the unknown system even when the input is a colored signal.

This paper propeses advanced multi-stage interference canceller systems (MSICS) wihch can estimate radio channels with precision in the direct sequence code division multiple access (DS-CDMA) systems. For the accurate channel estimations, we propose a novel radio channel estimation method specified by the following two signal processing methods. One is the radio channel estimation using both pilot and information signals. The other is the correction of estimated radio channels using adaptation algorithm based on the least mean square method (LMS). The results of our computer simulation indicate that the cell capacity of the advanced MSICS in serial and parallel structure can be increased by about 1.8 and 1.3 times over that of a receiver which does not has a canceller, respectively. Moreover, the advanced MSICS in serial and parallel structure can reduce the required Eb/No by about 1.2 dB and 1.6 dB at a BER of 10-3 compared to the Eb/No of a basic MSICS, respectively.

In addition to additive thermal noise, a received direct-sequence spread spectrum (DS/SS) signal may suffer from intersymbol interference (ISI) and interference caused by cochannel narrowband users or other narrowband radio frequency interference (RFI). This paper presents a workable solution for removing narrowband interference (NBI) and reducing ISI or inter-chip interference (ICI) when the communication channel can be modeled as an FIR filter and the NBI comes from multiple CW tones, an AR-modeled Gaussian process, or a BPSK signal. Unlike earlier solutions, the proposed scheme is capable of performing the functions of NBI-rejection, ISI/ICI suppression and data detection (code despreading) simultaneously. It is easy to implement and, more importantly, it yields lower bit error rate (BER) and smaller mean squared error (MSE).

It is well known that M-ary/spread spectrum (M-ary/SS) system is superior to direct-sequence spread spectrum system under AWGN, and can achieve high spectral efficiency. On the other hand, however, the main drawback of this system is that the synchronization acquisition is difficult. In this paper, we propose a new synchronization acquisition method of M-ary/SS system. This method acquires the code synchronization by introducing a symmetrical property in spreading sequences, and detecting this property with the differential decoding technique. As spreading sequences, a set of orthogonal sequences and a set of non-orthogonal sequences are considered. The strong features of proposed systems are that the systems can acquire the code synchronization in carrier band and can reduce the complexity of calculation greatly. Among the comparison results of the systems with newly proposed orthogonal and some specific non-orthogonal spreading sequences, it is especially noted that the latter can reduce the mean acquisition time and calculation complexity much greater than the former.

This paper proposes and investigates a vehicular radar system that can measure the distance to, the relative speed of and the direction of arrival (DOA) of the reflected waves from multiple targets or vehicles using the direct-sequence spread spectrum (DS-SS) technique. In particular, we propose a DOA estimation scheme using a multi-beam antenna. In order to show that the proposed system can accurately measure the above mentioned quantities, the performance is evaluated numerically in a multipath environment. Moreover, optimal multi-beam pattern is derived to minimize error probability of DOA estimation.

This paper proposes a novel synchronous acquisition method with an adaptive filter in asynchronous direct sequence/code division multiple access (DS/CDMA) communication systems. An adaptive filter is used in a single-user receiver, in complete synchronization of desired user's signal, the tap coefficients of the filter are controlled to orthogonalize to all other user's spreading sequences without knowledge of the sequences, amplitude and time delays of the signals. While, in the proposed system for synchronous acquisition, the tap coefficients are controlled to orthogonalize to all user's sequences including desired user's signal. The synchronous acquisition can be achieved by using the difference of cross-correlation function value between desired user's sequence of inphase and the tap coefficients for each phase. The principle and performance evaluation for the proposed method are shown. As a result, compared to an acquisition method of conventional sliding correlator, considerable improvement of the average acquisition time can be achieved in large power multiple access interference environment.

Pilot symbol-assisted (PSA) decision-directed coherent adaptive array diversity (CAAD) is proposed for increasing the reverse link capacity of DS-CDMA mobile radio systems. In the proposed scheme, PSA channel estimation is applied to coherent Rake combining, and the weights of the antenna array are adaptively updated using both pilot symbols and decision-directed data symbols after Rake combining as references for minimum mean squared error (MMSE) criteria. The reverse link capacity of a 3-sectored base station is evaluated by computer simulation when fast transmit power control (TPC) based on singal-to-interference plus backgound noise power ratio (SIR) measurement is applied under nultipath Rayleigh fading environments. It is shown that a 6-element (sector) CAAD receiver can increase the capacity to about 4.2 times that with a single antenna (per sector) receiver when links are interference-limited. The link capacity achievable with the 6-element CAAD receiver is 1.2 times that with a 6-branch antenna diversity reciever with antenna spacing of 10 carrier wavelengths, while significantly reducing the strong interference from high bit rate transmission (high transmit power) users.

In this paper, we present orthogonal multi-code CDMA systems with the constant amplitude transmission. In general, the dynamic range of the amplitude of the transmitting signal is very large in the case of orthogonal multi-code CDMA systems. In order to realize the constant amplitude transmission for orthogonal multi-code CDMA systems, we propose a constant amplitude coding. First, we show the basic concept of the constant amplitude coding. And then, we show that the constant amplitude transmission can be realized by the combination of the conventional orthogonal multi-code CDMA and the constant amplitude coding. Finally, the effectiveness of the proposed method is evaluated in terms of the bit error rate performance and it is shown that the proposed method is robust to the non-linear distortion caused by a high power amplifier (HPA).

A slotted ALOHA direct sequence spread spectrum system with random signatures is considered. The system is applicable in cases where a large number of terminals transmit to a single hub station like in cellular digital radio, personal mobile systems and wireless LANs. It is shown that significant improvements in packet throughput capacity are obtained if the adaptive receiver structures are used. Systems for the comparison are the spread spectrum slotted ALOHA system and the conventional slotted ALOHA system.

In this paper we propose a new far-field RCS prediction method using cylindrical or planar near-field RCS data. First we derive the relation between RCS and the scattering coefficient using physical optics technique. The far-field RCS prediction algorithm is obtained by approximating the relation using the condition of Fresnel region and the paraxial constraint of scanning angle in the case of cylindrical or planar scanning. Finally we predict the far-field RCS using measured or calculated near-field RCS data of the conducting rectangular prism or plate. The validity of the proposed algorithm is demonstrated.

The numerical property of the recursive least squares (RLS) algorithm has been extensively, studied. However, very few investigations are reported concerning the numerical behavior of the predictor-based least squares (PLS) algorithms which provide the same least squares solutions as the RLS algorithm. In Ref. [9], we gave a comparative study on the numerical performances of the RLS and the backward PLS (BPLS) algorithms. It was shown that the numerical property of the BPLS algorithm is much superior to that of the RLS algorithm under a finite-precision arithmetic because several main instability sources encountered in the RLS algorithm do not appear in the BPLS algorithm. This paper theoretically shows the stability of the BPLS algorithm by error propagation analysis. Since the time-variant nature of the BPLS algorithm, we prove the stability of the BPLS algorithm by using the method as shown in Ref. [6]. The expectation of the transition matrix in the BPLS algorithm is analyzed and its eigenvalues are shown to have values within the unit circle. Therefore we can say that the BPLS algorithm is numerically stable.

In this paper, we examine a new initial symbol acquisition method for M-ary spread-spectrum (M-ary/SS) signals that are affected by large carrier frequency offset. By the effect of the carrier frequency offset, preamble signal energy is dispersed to the undersired outputs. The proposed method is based on the collection of such dispersed signal energies by using reference patterns. The reference patterns are constructed by using the characteristic of Hadamard code sequences. The effectiveness of the proposed method is evaluated in terms of mean acquisition time.

This paper presents a method for land cover classification using the SIR-C/X-SAR imagery based on the maximum likelihood method and the polarimetric filtering. The main feature is to use polarimetric enhanced image information in the pre-processing stage for the classification of SAR imagery. First, polarimetric filtered images are created where a specific target is enhanced versus another, then the image data are incorporated into the feature vector which is essential for the maximum likelihood classification. Specific target classes within the SAR image are categorized according to the maximum likelihood method using the wavelet transform. Addition of polarimetric enhanced image in the preprocessing stage contributes to the increase of classification accuracy. It is shown that the use of polarimetric enhanced images serves efficient classifications of land cover.

In this paper, we propose a two-dimensional (2-D) least-squares lattice (LSL) algorithm for the general case of the autoregressive (AR) model with an asymmetric half-plane (AHP) coefficient support. The resulting LSL algorithm gives both order and space recursions for the 2-D deterministic normal equations. The size and shape of the coefficient support region of the proposed lattice filter can be chosen arbitrarily. Furthermore, the ordering of the support signal can be assigned arbitrarily. Finally, computer simulation for modeling a texture image is demonstrated to confirm the proposed model gives rapid convergence.

In the last few years analog adaptive filters have been a subject of active research because they have the ability to handle in real time much higher frequencies, with a smaller size and lower power consumption that their digital counterparts. During this time several analog adaptive filter algorithms have been reported in the literature, almost all of them use the continuous time version of the least mean square (LMS) algorithm. However the continuous time LMS algorithm presents the same limitations than its digital counterpart, when operates in noisy environments, although their convergence rate may be faster than the digital versions. This fact suggests the necessity of develop analog versions of recursive least square (RLS) algorithm, which in known to have a very low sensitivity to additive noise. However a direct implementation of the RLS in analog way would require a considerable effort. To overcome this problem, we propose an analog RLS algorithm in which the adaptive filter coefficients vector is estimated by using a fully connected network that resembles a Hopfield network. Theoretical and simulations results are given which show that the proposed and conventional RLS algorithms have quite similar convergence properties when they operate with the same sampling rate and signal-to-noise ratio.

A rigorous radar cross section (RCS) analysis is carried out for two-dimensional rectangular and circular cavities with double-layer material loading by means of the Wiener-Hopf (WH) technique and the Riemann-Hilbert problem (RHP) technique, respectively. Both E and H polarizations are treated. The WH solution for the rectangular cavity and the RHP solution for the circular cavity involve numerical inversion of matrix equations. Since both methods take into account the edge condition explicitly, the convergence of the WH and RHP solutions is rapid and the final results are valid over a broad frequency range. Illustrative numerical examples on the monostatic and bistatic RCS are presented for various physical parameters and the far field scattering characteristics are discussed in detail. It is shown that the double-layer lossy meterial loading inside the cavities leads to the significant RCS reduction.

Fractals provide a good description of natural scenes and objects based on their statistically self-similar property. They are also used to discriminate natural or man-made objects because natural objects have a better fitting to the fractional Brownian motion (fBm) model than artificial objects. Sea clutter as natural phenomena well fit to the fBm to induce little error. On the other hand, targets as man-made objects induce much more error because they frequently deviate from the fBm model. Therefore, the fractal error has a good characteristic to detect targets buried in clutter. We modified the fractal error defined by Cooper to be suitable for radar image processing. For the X-band radar image, the performance of our proposed method is comparable to that of the Cooper's method. For the millimeter wave (MMW) radar images, our method is better than the Cooper's one.

A new adaptive rate control with congestion prediction is developed that is highly robust against long propagation delays. It minimizes the network performance degradation caused by the delay based on prediction by extrapolating past data and correction using new notification. The simulation results show that our proposed control maintains high throughput and a smaller buffer even in long propagation delay networks, like ATM-WAN.

One of the polarimetric radar applications is classification or identification of targets making use of the scattering matrix. This paper presents a decomposition scheme of a scattering matrix into three elementary scattering matrices in the circular polarization basis. The elementary components are a sphere, a diplane (dihedral corner reflector), and a helix. Since a synthetic aperture FM-CW radar provides scattering matrix through a polarimetric measurement, this decomposition scheme was applied to the actual raw data, although the matrix is resulted from a swept frequency measurement. Radar imaging experiments at the Ku band (14.5-15.5GHz) were carried out to obtain a total of 6464 scattering matrices in an imaging plane, using flat plates, corner reflectors and wires as elementary radar targets for classification. It is shown that the decomposition scheme has been successfully carried out to distinguish these targets and that the determination of rotation angle of line target is possible if the scattering matrix is classified as a wire.