This paper describes a method for estimating Direction Of Arrival (DOA) of multiple sound sources in full azimuth with three microphones. Estimating DOA with paired microphone arrays creates imaginary sound sources because of time delay of arrival (TDOA) being identical between real and imaginary sources. Imaginary sound sources can create chronic problems in multiple Sound Source Localization (SSL), because they can be localized as real sound sources. Our proposed approach is based on the observation that each microphone array creates imaginary sound sources, but the DOA of imaginary sources may be different depending on the orientation of the paired microphone array. With the fact that a real source would always be localized in the same direction regardless of the array orientation, we can suppress the imaginary sound sources by minimum filtering based on Steered Response Power – Phase Transform (SRP-PHAT) method. A set of experiments conducted in a real noisy environment showed that the proposed method was accurate in localizing multiple sound sources.

We propose an implementation of the tapped delay line adaptive array (TDLAA) at the base station for improving the BER performance of asynchronous multi-user mobile communication over fast fading channels using multiple antennas. The data of each user at the mobile station, which applies two transmit antennas, are encoded by Space Time Block Code (STBC). The proposed scheme transmits the pilot signal and information data in alternate time slots. We derive performance criteria for designing such a scheme under the assumption that the fading is classified as fast fading. We show that the proposed scheme can suppress co-channel interference (CCI) and defeat Doppler spread effectively.

Many parallel Fast Fourier Transform (FFT) algorithms adopt multiple stages architecture to increase performance. However, data permutation between stages consumes volume memory and processing time. One FFT array processing mapping algorithm is proposed in this paper to overcome this demerit. In this algorithm, arbitrary 2k butterfly units (BUs) could be scheduled to work in parallel on n=2s data (k=0,1,..., s-1). Because no inter stage data transfer is required, memory consumption and system latency are both greatly reduced. Moreover, with the increasing of BUs, not only does throughput increase linearly, system latency also decreases linearly. This array processing orientated architecture provides flexible tradeoff between hardware cost and system performance. In theory, the system latency is (s2s-k)tclk and the throughput is n/(s2s-ktclk), where tclk is the system clock period. Based on this mapping algorithm, several 18-bit word-length 1024-point FFT processors implemented with TSMC0.18 µm CMOS technology are given to demonstrate its scalability and high performance. The core area of 4-BU design is 2.9911.121 mm2 and clock frequency is 326 MHz in typical condition (1.8 V,25). This processor completes 1024 FFT calculation in 7.839 µs.

In this paper, we propose a spatio-temporal equalizer for the space-time block coded transmission over the frequency selective fading channels with the presence of co-channel interference (CCI). The proposed equalizer, based on the tapped delay line adaptive array (TDLAA), performs signal equalization and CCI suppression simultaneously using the minimum mean square error (MMSE) method. It is to show that our scheme outperforms the previous two-stage combined adaptive antenna and delayed decision feedback sequence estimator (DDFSE) approach. We also show that performance can be further improved if the synchronization between the preceding and delayed paths is achieved.

We propose a new algorithm for overdetermined blind source separation (BSS) based on multistage independent component analysis (MSICA). To improve the separation performance, we have proposed MSICA in which frequency-domain ICA and time-domain ICA are cascaded. In the original MSICA, the specific mixing model, where the number of microphones is equal to that of sources, was assumed. However, additional microphones are required to achieve an improved separation performance under reverberant environments. This leads to alternative problems, e.g., a complication of the permutation problem. In order to solve them, we propose a new extended MSICA using subarray processing, where the number of microphones and that of sources are set to be the same in every subarray. The experimental results obtained under the real environment reveal that the separation performance of the proposed MSICA is improved as the number of microphones is increased.

A new algorithm, termed reduced-order Root-MUSIC, for high resolution direction finding is proposed. It requires finding all the roots of a polynomial with an order equaling twice the number of propagating signals. Some Monte Carlo simulations are used to test the effectiveness of the proposed algorithm.

A constant modulus adaptive array algorithm is derived using analysis and synthesis filter banks to permit adaptive digital beamforming for wideband signals. The properties of the CMA adaptive array using the filter banks are investigated. This array would be used to realize adaptive digital beamforming when this is difficult by means of ordinary (that is, non-subband) processing due to the limited speed of signal processor operations. As an actual application, we present a beamspace adaptive array structure that combines the analysis and synthesis filter banks with RF-domain multibeam array antennas, such as those utilizing optical signal processing.

High resolution algorithms in sensor arrays lead to accurate results but with expensive eigendecompositions making its use in real-time applications such as mobile communications relatively difficult. In this paper, a trade-off between accuracy and computational load is accomplished through a simplified algorithm which instead of eigendecompositions, uses the robust QR decomposition for which many effcient parallel (systolic, wavefront array) implementations exist. First, a simple detection scheme is presented and, through simulations, is shown to work very well for sufficient SNR, even when signals are coherent. Outputs of the detection process include simultaneously estimates of signals Direction Of Arrivals (DOA's) and a simple beamformer vector resulting in an estimate of the desired signal. Extensive simulations are performed assuming different scenarios of variations in SNR, DOA's leading to discussions on the possibilities and limitations of the proposed solution.

When signal subspace techniques, such as MuSIC, are used to locate a number of incident signals, an exhaustive search of the array manifold has to be carried out. This search involves the evaluation of a single cost function at a number of points which form a grid, resulting in quantization-error effects. In this paper a new algorithm is put forward to overcome the quantization problem. The algorithm uses a number of cost functions, and stages, equal to the number of incident signals. At each stage a new cost function is evaluated in a small number of "special" directions, known as characteristic points. For an N-element array the characteristic points, which can be pre-calculated from the array manifold curvatures, partition the array manifold into N-1 regions. By using a simple gradient algorithm, only a small area of one of these regions is searched at each stage, demonstrating the potential benefits of the proposed approach.

A high resolution iterative algorithm for estimating the direction-of-arrival of multiple wide band sources is proposed in this paper. For equally spaced array structure, two Unitary Transform based approaches are proposed in frequency domain for signal subspace processing in both coherent multipath and incoherent environment. Given a priori knowledge of the initial estimates of DOA, with proper spatial prefiltering to separate multiple groups of closely spaced sources, our proposed algorithm is shown to have high resolution capability even in coherent multipath environment without reducing the angular resolution, compared with the use of subarray. Compared with the conventional algorithm, the performance by the proposed algorithm is shown by the simulations to be improved under low Signal to Noise Ratio (SNR) while the performance is not degraded under high SNR. Moreover the computation burden involved in the eigencomputation is largely reduced by introducing the Pesudo-Hermitian matrix approximation.