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We present an iterative method for joint antenna-array calibration and direction of arrival estimation using millimeter-wave (mm-Wave) radar operating at 77 GHz. The calibration compensates for antennaarray coupling, and phase and gain errors, and does not require any training data. This method is well suited for applications, such as automotive radars, where multiple antenna elements are packaged...
We propose a new method to detect double-talk and control filter adaptation in an acoustic echo canceller (AEC). The method is based on computing the zero-crossings rate (ZCR) of the AEC output and comparing it against a suitably-chosen threshold. As the ZCR values falls below the threshold, double talk is declared and the AEC filter adaptation is either slowed down or halted. The zero crossings are...
Blind system identification is important for a wide range of applications. The conditional maximum likelihood (CML) method is one of the most effective ones recently developed for blind system identification. In particular, the CML method is statistically most efficient at relatively high signal-to-noise ratios (SNR). Unfortunately, the original implementation of the CML method via the two-step maximum...
This paper presents a new paradigm of solving the non-linear acoustic echo cancellation problem. The non-linear echo path is modeled by a memoryless non-linearity followed by a linear FIR filter. The problem is cast into a state-space framework and solved using a cascade of Kalman filters in time domain, one filter adapting to the linear echo path and the other filter adapting to the memoryless non-linearity...
We present a new method for data association in 3-D object tracking for automotive applications. The method is a variant of the nearest-neighbor data association and is based on comparing the location of an existing track with that of each incoming object and associating to the one which is closest in 3-D space. As a pair is associated, it is removed from the search space and the association process...
This paper presents a new 3-D tracking method for millimeter-wave radar imaging of objects around a car in advanced driving assistance systems (ADAS). Current automotive radar systems only estimate objects in 2-D plane (range and azimuth) and hence only a 2-D tracking is employed. We expect future evolutions of these systems to provide the additional elevation information allowing a 3-D view around...
We explore interesting connections between blind source separation (BSS) and acoustic echo cancellation (AEC), and develop a framework where the AEC problem is transformed and solved as a BSS problem. We show that by careful selection of the BSS algorithm the double-talk (DT) problem in AEC is solved without the need to use a DT detector or a step-size controller. Furthermore, the echo cancellation...
The proportionate normalized least-mean squares (PNLMS) adaptation algorithm exploits the sparse nature of acoustic impulse responses and assigns adaptation gain proportional to the absolute value of filter coefficients, thereby resulting in faster convergence. In the past it has shown to improve convergence of acoustic paths in echo-cancellation applications. In this paper, we investigate the use...
For cell-phone applications, single microphone noise suppression techniques have limited performance at very low SNR (close to 0 dB). In certain cases, they also suffer from the artifacts of nonlinear processing. In this paper, we will show that techniques based on two-microphone blind source separation (BSS) algorithm provide significant interference suppression for cell-phone applications, particularly...
In this work, we explore important connections between blind source separation (BSS) and ideal beamforming. We first compare the performance of a null-steering beamformer against that of a frequency-domain BSS method in a reverberant environment, drawing some interesting conclusions. We then examine the feasibility of using beamformer concepts to resolve permutation inconsistency across frequency,...
This paper addresses the issue of detection and parameter estimation of multicomponent polynomial phase signals (mc-PPS) embedded in noise. We focus on analyzing a general class of mc-PPS in the sense that we allow the PPS to have (i) very different amplitudes, (ii) unknown phase orders, and (iii) unknown number of components. We first show how existing techniques are inadequate in providing reliable...
We present a technique based on the quadratic phase transform (QPT) for joint phase parameter estimation of multicomponent chirp signals. The QPT has the ability to analyze chirp signals in the same way as Fourier transform analyzes sinusoidal signals. In view of its practical implementation, a discrete version of the QPT, called the discrete quadratic phase transform (DQPT), is introduced. A novel...
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