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We propose a time-domain multiple sound source localization (SSL) method based on Bayesian inference. This method is specifically designed to run on the stochastic machines (SM) that we are currently developing to perform efficient low-level sensor signal processing with ultra-low power consumption. The proposed SSL method is divided into two main parts. First, a probabilistic model is run on 50 very short time frames (3. 75ms each) of multichannel recorded signals. Second, the results obtained on the different frames are fused to obtain a final localization map. Using the system in a supervised way allows to extract estimated source locations by selecting as many maxima as there are sources in the room. We explain how this method is implemented on a SM. Experiments are presented to illustrate the performance and robustness of the resulting system.

In this paper, an improved azimuth angle estimation method with a single acoustic vector sensor (AVS) is proposed based on matched filtering theory. The proposed method is mainly applied in an active sonar detection system. According to the conventional passive method based on complex acoustic intensity measurement, the mathematical and physical model of this proposed method is described in detail. The computer simulation and lake experiments results indicate that this method can realize the azimuth angle estimation with high precision by using only a single AVS. Compared with the conventional method, the proposed method achieves better estimation performance. Moreover, the proposed method does not require complex operations in frequency-domain and achieves computational complexity reduction.

A new method for measuring the pressure reflection coefficient in a buffer rod configuration is presented, together with experimental results for acoustic measurements of the liquid density, based on the measurement of the liquid's acoustic impedance. The method consists of using 2 buffers enclosing the liquid in a symmetrical arrangement with a transducer fixed to each buffer. One of the transducers is used in a pulse-echo mode while the other transducer operates as a receiver. The echo amplitudes leading to the pressure reflection coefficient as found by this method possess advantages such as reduced attenuation due to a shorter liquid transmission path and reduced interference, as compared with the ABC method. Measurements with distilled water and with special density calibration oil qualities have been performed using both the new method and the ABC method and are shown for the new method to give a density span within +/- 0.15% of the reference values. A comparison of the measured densities based on both a time-domain and a l(2)-norm frequency domain integration signal processing approach is given, along with a recommendation as to how the signal processing should be performed.

High peak-to-average-power ratio (PAPR) is a particular disadvantage of orthogonal frequency-division multiplexing (OFDM) systems and can significantly degrade the power efficiency at the transmitter. The aim of this paper is to propose a post-inverse fast Fourier transform (IFFT) PAPR reduction method based on intelligent linear symbol combining with the objective to minimize the PAPR at the transmitter. Unlike the methods so far reported in the literature, the proposed method has a relatively low complexity and does not require external randomization sequences. This paper will also investigate the impact of the proposed method on the system's bit error rate (BER) performance and provide a closed-form analytical expression that takes into account the BER dependency on the side information bits and multiblock combination. It will be shown that the proposed technique can provide significant PAPR reductions at manageable levels of signal processing requirements while the BER degradation is relatively small. © 2008 IEEE.

This paper presents a distributed approach for time- domain focusing, which significantly enhances the overall efficiency by distributing the computational load across a (potentially large) number of networked computers. The system described includes the so-called master, responsible for pre-processing, the distribution of fragments of raw-data data and the collection of processed image fragments. Fragments of raw-data are passed to so-called slaves, any number of which can be connected to the master, which are responsible for the focusing itself. Master and slave actively communicate over the network to organise the entire process in a scalable manner. In this way, time-domain processing can be accelerated by a factor that is virtually linear in the number of participating slaves. This paper summarises the current status of software development, realised in a platform-independent way using the IDL and Java languages. Additionally, some preliminary evaluations of performance, scalability and the required network infrastructure are given. Some examples of SAR data, acquired by the airborne sensor E-SAR of DLR, and processed with the system described are shown.

A pilot sequence design for MIMO-OFDM systems is investigated where all transmit antennas share the same sub-carriers to convey pilot symbols. The pilot sequences are endowed with phase-shifting properties, granting the receiver the possibility of extracting the impulse responses for all channels directly from the antennas’ time-domain received signals, without co-channel interference. A linear processing of the timedomain samples is all that is needed to get the channel impulse responses, resulting in an algorithm with very low computational load. The feasibility of the investigated method is substantiated by system simulation using indoor and outdoor broadband wireless channel models.