A triangular decomposition-based multipath super-resolution method is proposed to improve the range resolution of small unmanned aerial vehicle (UAV) radar altimeters that use a single channel with continuous direct spread waveform. In the engineering applications of small UAV radar altimeter, multipath scenarios are quite common. When the conventional matched filtering process is used under these environments, it is difficult to identify multiple targets in the same range cell due to the overlap between echoes. To improve the performance, we decompose the overlapped peaks yielded by matched filtering into a series of basic triangular waveforms to identify various targets with different time-shifted correlations of the pseudo-noise (PN) sequence. Shifting the time scale enables targets in the same range resolution unit to be identified. Both theoretical analysis and experiments show that the range resolution can be improved significantly, as it outperforms traditional matched filtering processes.

The sound power level is a physical quantity indispensable for evaluating the amount of sound energy radiated from electrical and mechanical apparatuses. The precise determination of the sound power level requires the qualification of the measurement environment, such as a hemi-anechoic room, by estimating the deviation of the sound pressure level from the inverse-square law. In this respect, Annex A of ISO 3745 specifies the procedure for room qualification and defines a tolerance limit for the directivity of the sound source, which is used for the qualification. However, it is impractical to prepare a special loudspeaker only for room qualification. Thus, we developed a simulation method to investigate the influence of the sound source directivity on the measured deviation of the sound pressure level from the inverse-square law by introducing a quantitative index for the influence of the directivity. In this study, type 4202 reference sound source by Brüel & Kjær was used as a directional sound source because it has been widely used as a reference standard for the measurement of sound power levels. We experimentally obtained the directivity of the sound source by measuring the sound pressure level over the measurement surface. Moreover, the proposed method was applied to the qualification of several hemi-anechoic rooms, and we discussed the availability of a directional sound source for the process. Analytical results showed that available reference sound sources may be used for the evaluation of hemi-anechoic rooms depending on the sound energy absorption coefficient of the inner wall, the directionality of the microphone traverse, and the size of the space to be qualified. In other words, the results revealed that a reference sound source that is once quantified by the proposed method can be used for qualifying hemi-anechoic rooms.

For the nonlinear acoustic echo cancellation, we present an algorithm to estimate the threshold of the clipping effect and the room impulse response vector by suppressing their time-varying cost function. A common way to suppress the time-varying cost function of a pair of parameters is to alternatingly minimize the function with respect to each parameter while keeping the other fixed, which we refer to as adaptive alternating minimization. However, since the cost function for the threshold is nonconvex, the conventional methods approximate the exact minimizations by gradient descent updates, which causes serious degradation of the estimation accuracy in some occasions. In this paper, by exploring the fact that the cost function for the threshold becomes piecewise quadratic, we propose to exactly minimize the cost function for the threshold in a closed form while suppressing the cost function for the impulse response vector in an online manner, which we call exact-online adaptive alternating minimization. The proposed method is expected to approximate more efficiently the adaptive alternating minimization strategy than the conventional methods. Numerical experiments demonstrate the efficacy of the proposed method.

Antenna radiation patterns have side-lobes that add to ambiguity in the form of ghosting and object repetition in SAR images. An L-band 1.27GHz, 2×5 element proximity-coupled corner-truncated patch array antenna synthesized using the Dolph-Chebyshev method to reduce side-lobe levels is proposed. The designed antenna was sim-ulated, optimized, and fabricated for antenna performance parameter measurements. Antenna performance characteristics show good agree-ment with simulated results. A set of antennas were fabricated and then used together with a custom synthetic aperture radar system and SAR imaging performed on a point target in an anechoic chamber. Imaging results are also discussed in this paper showing improvement in image output. The antenna and its connected SAR systems developed in this work are different from most previous work in that this work is utilizing circular polarization as opposed to linear polarization.

Determining an effective way to reduce computation complexity is an essential task for adaptive echo cancellation applications. Recently, a family of partial update (PU) adaptive algorithms has been proposed to effectively reduce computational complexity. However, because a PU algorithm updates only a portion of the weights of the adaptive filters, the rate of convergence is reduced. To address this issue, this paper proposes an enhanced switching-based variable step-size (ES-VSS) approach to the M-max PU least mean square (LMS) algorithm. The step-size is determined by the correlation between the error signals and their noise-free versions. Noise-free error signals are approximated according to the level of convergence achieved during the adaptation process. The approximation of the noise-free error signals switches among four modes, such that the resulting step-size is as close to its optimal value as possible. Simulation results show that when only a half of all taps are updated in a single iteration, the proposed method significantly enhances the convergence rate of the M-max PU LMS algorithm.

Hands-free communications between cellular phones must be robust enough to withstand echo-path variation, and highly nonlinear echoes must be suppressed at low cost, when acoustic echo cancellation or suppression is applied to them. This paper proposes a spectrum-selective nonlinear echo suppression (SS-ES) approach as a solution to these issues. SS-ES is characterized by the selection of either a spectrum of the residual signal from an adaptive filter or a spectrum of the sending input signal depending on the amount of linear echo cancellation in an adaptive filter. Compared to conventional methods, the objective evaluation results of the SS-ES approach show an improvement of approximately 0.8-2.2dB, 0.23-2.39dB, and 0.26-0.50 in average echo return loss enhancement (ERLE), average root-mean-square log-spectral distortion (RMS-LSD), and the perceptual evaluation of speech quality (PESQ) value, respectively, under echo-path variation and double-talk conditions.

An echo-hiding scheme is presented to detect the pitch variation due to playback speed modification. The inserted time-spread echo is obtained by convolving the highpass filtered audio with a gain-controlled pseudo noise sequence. The perceptual evaluation confirms that the embedded echo is virtually imperceptible. Compared with the Fourier magnitude modulation, the proposed scheme attains better detection rates.

The separation time-overlapping ultrasound signals is necessary to obtain accurate estimate of transit time and material properties. In this letter, a method to determine the optimal transform order of fractional Fourier transform (FRFT) for decomposition of overlapping ultrasonic signals is proposed. The optimal transform order is obtained by minimizing the mean square error (MSE) between the output and the reference signal. Furthermore, windowing in FRFT domain is discussed. Numerical simulation results show the performances of the proposed method in separating signals overlapping in time.

In this paper, we propose a use of the group sparsity in adaptive learning of second-order Volterra filters for the nonlinear acoustic echo cancellation problem. The group sparsity indicates sparsity across the groups, i.e., a vector is separated into some groups, and most of groups only contain approximately zero-valued entries. First, we provide a theoretical evidence that the second-order Volterra systems tend to have the group sparsity under natural assumptions. Next, we propose an algorithm by applying the adaptive proximal forward-backward splitting method to a carefully designed cost function to exploit the group sparsity effectively. The designed cost function is the sum of the weighted group l1 norm which promotes the group sparsity and a weighted sum of squared distances to data-fidelity sets used in adaptive filtering algorithms. Finally, Numerical examples show that the proposed method outperforms a sparsity-aware algorithm in both the system-mismatch and the echo return loss enhancement.

In this paper, we propose a step size control method capable of quickly canceling acoustic echo even when double talk continues from the echo path change. This method controls the step size by substituting the norm of the difference vector between the coefficient vectors of a main adaptive filter (Main-ADF) and a sub-adaptive filter (Sub-ADF) for the estimation error provided by the former. Actually, the number of taps of Sub-ADF is limited to a quarter of that of Main-ADF, and the larger step size than that applied to Main-ADF is given to Sub-ADF; accordingly the norm of the difference vector quickly approximates to the estimation error. The estimation speed can be improved by utilizing the norm of the difference vector for the step size control in Main-ADF. We show using speech signals that in single talk the proposed method can provide almost the same estimation speed as the method whose step size is fixed at the optimum one and verify that even in double talk the estimation error, quickly decreases.

A new wideband wave absorber with translucent structure using carbon fibers is presented in this paper. The absorber is composed of bundled short carbon fibers which are arranged in front of a back metal and a spacer. Absorption characteristics of the one-layered absorber showed that matching frequencies can be controlled by the thickness of the spacer and the length of the carbon fibers. To further improve the characteristics, multi-layered absorbers are designed with the same procedure as one-layered absorber. The designed absorber showed 15 dB absorption characteristics from 1.0 to 10.0 GHz. Then a small anechoic chamber with the inside dimension of 200 cm200 cm200 cm was fabricated using ninety-six proposed absorbers. The electrical power in the chamber was measured at 2.45 GHz and the results showed that the variation of the power was less than 4 dB inside a circle with radius of 60 cm as work space for electromagnetic measurements.

Regularization plays a fundamental role in adaptive filtering. There are, very likely, many different ways to regularize an adaptive filter. In this letter, we propose one possible way to do it based on a condition that makes intuitively sense. From this condition, we show how to regularize the recursive least-squares (RLS) algorithm.

This paper presents a single-chip speech dialogue module and its evaluation on a personal robot. This module is implemented on an application processor that was developed primarily for mobile phones to provide a compact size, low power-consumption, and low cost. It performs speech recognition with preprocessing functions such as direction-of-arrival (DOA) estimation, noise cancellation, beamforming with an array of microphones, and echo cancellation. Text-to-speech (TTS) conversion is also equipped with. Evaluation results obtained on a new personal robot, PaPeRo-mini, which is a scale-down version of PaPeRo, demonstrate an 85% correct rate in DOA estimation, and as much as 54% and 30% higher speech recognition rates in noisy environments and during robot utterances, respectively. These results are shown to be comparable to those obtained by PaPeRo.

In this Letter, a residual acoustic echo suppression method is proposed to enhance the speech quality of hands-free communication in an automobile environment. The echo signal is normally a human voice with harmonic characteristics in a hands-free communication environment. The proposed algorithm estimates the residual echo signal by emphasizing its harmonic components. The estimated residual echo is used to obtain the signal-to-interference ratio (SIR) information at the acoustic echo canceller output. Then, the SIR based Wiener post-filter is constructed to reduce both the residual echo and noise. The experimental results confirm that the proposed algorithm is superior to the conventional residual echo suppression algorithm in terms of the echo return loss enhancement (ERLE) and the segmental signal-to-noise ratio (SEGSNR).

This letter proposes a windowing frequency domain adaptive algorithm, which reuses the filtering error to apply window function in the filter updating symmetrically. By using a proper window function to reduce the negative influence of the spectral leakage, the proposed algorithm can significantly improve the performance of the acoustic echo cancellation for speech signals.

This letter proposes a new hybrid EM wave absorber with the crossed-wedge shape, which can be applied to 3 m semi anechoic chambers. In this study, we designed a new hybrid EM wave absorber with the crossed-wedge shape, which consisted of the inorganic and organic thin corrugated dielectric lossy sheet containing organic conductive fibers. Then the 3 m semi anechoic chamber is constructed in the size of 9.0 m6.0 m5.7 m (LWH) using these absorbers, and also the normalized site attenuation (NSA) is measured according to ANSI C63.4 in the frequency range of 30 MHz to 1 GHz. As a result, the measured NSA is obtained within 3 dB of the theoretical one.

This paper proposes an enhanced method for estimating the a priori Signal-to-Disturbance Ratio (SDR) to be employed in the Acoustic Echo and Noise Suppression (AENS) system for full-duplex hands-free communications. The proposed a priori SDR estimation technique is modified based upon the Two-Step Noise Reduction (TSNR) algorithm to suppress the background noise while preserving speech spectral components. In addition, a practical approach to determine accurately the Echo Spectrum Variance (ESV) is presented based upon the linear relationship assumption between the power spectrum of far-end speech and acoustic echo signals. The ESV estimation technique is then employed to alleviate the acoustic echo problem. The performance of the AENS system that employs these two proposed estimation techniques is evaluated through the Echo Attenuation (EA), Noise Attenuation (NA), and two speech distortion measures. Simulation results based upon real speech signals guarantee that our improved AENS system is able to mitigate efficiently the problem of acoustic echo and background noise, while preserving the speech quality and speech intelligibility.

Code density is often a critical issue in embedded computers, since the memory size of embedded systems is strictly limited. Echo instructions have been proposed as a method for reducing code size. This paper presents a new type of echo instruction, split echo, and evaluates an implementation of both split echo and traditional echo instructions on a MIPS R3000 based processor. Evaluation results show that memory requirement is reduced by 12% on average with small additional hardware cost.

A simple and novel residual acoustic echo cancellation method that employs binary masking is proposed to enhance the speech quality of hands-free communication in an automobile environment. In general, the W-disjoint orthogonality assumption is used for blind source separation using multi-microphones. However, in this Letter, it is utilized to mask the residual echo component in the time-frequency domain using a single microphone. The experimental results confirm the effectiveness of the proposed method in terms of the echo return loss enhancement and speech enhancement.

To attain good performance in an acoustic echo cancellation system, it is important to have a variable step size (VSS) algorithm as part of an adaptive filter. In this paper, we are concerned with the development of a VSS algorithm for a recently proposed subband affine projection (SAP) adaptive filter. Two popular VSS algorithms in the literature are the methods of delayed coefficients (DC) and variable regularization (VR). However, the merits and demerits of them are mutually exclusive. We propose a VSS algorithm that is a hybrid of both methods and combines their advantages. An extensive study of the new algorithm in different scenarios like the presence double-talk (DT) during the transient phase of the adaptive filter, DT during steady state, and varying DT power is conducted and reasoning is given to support the observed behavior. The importance of the method of VR as part of a VSS algorithm is emphasized.