Xuyang Chen

UWB Echo Signal Detection With Ultra-Low Rate Sampling Based on Compressed Sensing

A major challenge in ultra-wide-band (UWB) signal processing is the requirement for very high sampling rate. The recently emerging compressed sensing (CS) theory makes processing UWB signal at a low sampling rate possible if the signal has a sparse representation in a certain space. Based on the CS theory, a system for sampling UWB echo signal at a rate much lower than Nyquist rate and performing signal detection is proposed in this paper. First, an approach of constructing basis functions according to matching rules is proposed to achieve sparse signal representation because the sparse representation of signal is the most important precondition for the use of CS theory. Second, based on the matching basis functions and using analog-to-information converter, a UWB signal detection system is designed in the framework of the CS theory. With this system, a UWB signal, such as a linear frequency-modulated signal in radar system, can be sampled at about 10% of Nyquist rate, but still can be reconstructed and detected with overwhelming probability. The simulation results show that the proposed method is effective for sampling and detecting UWB signal directly even without a very high-frequency analog-to-digital converter.

A simple design method of linear-phase nonuniform filter banks with integer decimation factors

In this paper, we propose a simple method for designing linear-phase (LP) nonuniform filter banks (NUFBs) with integer decimation factors. The NUFBs are constructed in a direct structure. We derive a design criterion for the NUFB. With this criterion, the NUFBs can be designed simply and efficiently. By using the proposed method, near-perfect-reconstruction LP NUFBs with high stopband attenuation are obtained.

High-Resolution Imaging Via Moving Random Exposure and Its Simulation

In this correspondence, we introduce a new imaging method to obtain high-resolution (HR) images. The image acquisition is performed in two stages, compressive measurement and optimization reconstruction. In order to reconstruct HR images by a small number of sensors, compressive measurements are made. Specifically, compressive measurements are made by a low-resolution (LR) camera with randomly fluttering shutter, which can be viewed as a moving random exposure pattern. In the optimization reconstruction stage, the HR image is computed by different models according to the prior knowledge of scenes. The proposed imaging method offers a new way of acquiring HR images of essentially static scenes when the camera resolution is limited by severe constraints such as cost, battery capacity, memory space, transmission bandwidth, etc. and when the prior knowledge of scenes is available. The simulation results demonstrate the effectiveness of the proposed imaging method.

Recent Advances and New Design Method in Nonuniform Filter Banks

This paper mainly presents some recent advances in designing nonuniform filter banks (NUFBs), including direct and indirect methods, along with the detailed review on the typical design methods. Starting with the description of the motivations behind using NUFBs in real applications, we identify some problems existing in the current work. As a new contribution, we then propose a simple design method of near perfect reconstruction (NPR) NUFBs with a linear phase (LP) property called partial cosine modulation. Here we design the first and last analysis/synthesis filters separately, while obtaining the others via cosine modulation of several prototype filters. A design example is given to demonstrate the effectiveness and simplicity of this approach

Signal matching wavelet for ultrasonic flaw detection in high background noise

The wavelet transform (WT) is widely used in ultrasonic flaw detection (UFD) systems because of its property of multiresolution time-frequency analysis. Those traditional WT-based methods for UFD use a wavelet basis with limited types to match various echo signals (called wavelet matching signals), so it is difficult for those methods to achieve the optimal match between echo signal and wavelet basis. This results in limited detection ability in high background noise for those WT-based methods. In this paper, we propose a signal matching wavelet (SMW) method for UFD to solve this problem. Unlike traditional UFD systems, in the proposed SMW, the transmitted signal is designed to be a wavelet function for matching a wavelet basis. This makes it possible to obtain the optimal match between the echo signal and the wavelet basis. To achieve the optimal match from the aspect of energy, we derive three rules for designing the transmitted signal and selecting the wavelet basis. Further, the parameter selection in applying the proposed SMW method to a practical UFD system is analyzed. In addition, a low-rate discrete WT structure is designed to decrease the hardware cost, which facilitates the practical application of the proposed SMW. The simulation results show that the proposed SMW can efficiently detect flaws in high background noise even with SNR lower than -20 dB, outperforming the existing methods by 5 dB.

Direct Design of Near Perfect Reconstruction Linear Phase Nonuniform Filter Banks with Rational Sampling Factors

A direct method of designing linear phase (LP) near perfect reconstruction (NPR) nonuniform filter banks (NUFBs) with rational sampling factors is presented. Conditions on the possible sampling factors of NUFBs are given. The band position relations and phase relations of the significant aliasing components are also analyzed. Based on these two relations, we derive a necessary condition on the elimination of significant aliasing distortion (ALD). Meanwhile LP property is met. Moreover, a set of relations of the filters are presented to minimize the ALD further. In our proposed method, the LP NUFBs with high stopband attenuation and low system delay can be easily designed without nonlinear optimization procedure

Design of Linear-Phase Nonuniform Filter Banks With Partial Cosine Modulation

The majority of the existing work on designing nonuniform filter banks (NUFBs) cannot achieve linear-phase (LP) property, because of the high complexity associated with phase distribution. This correspondence proposes an idea of partial cosine modulation to obtain the LP property of NUFBs with rational sampling factors. It makes the efficient modulation technique possible to be used to design LP NUFBs. Except the separately designed lowpass and highpass analysis/synthesis filters, we obtain the bandpass by cosine modulation of several prototypes, worth of the name ¿partial cosine modulation.¿ By analyzing the phase issue of significant aliasing terms, we derive the matching conditions to make the required LP NUFB achievable. With these criteria being satisfied, the design problem becomes that of several prototypes as well as the lowpass and highpass filters, leading to a less design effort. By using the proposed method, near-perfect-reconstruction LP NUFBs can be obtained in a simple and efficient way as demonstrated by examples.

Optimal prototype filters for near-perfect-reconstruction cosine-modulated filter banks

In this paper, we propose a simple method for designing M-channel near-prefect-reconstruction (NPR) cosine-modulated filter banks (FBs). By employing the Parks-McClellan algorithm in constructing the prototype filter, an ideal magnitude response of the filter is achieved. Furthermore, the transition band of the prototype filter is constrained in such a way that it follows a cosine function. As a result, the FBs are approximately power complementary and therefore possess the NPR property. There are two main advantages in our proposed method. The first one is that no objective function in the optimization is explicitly required and the second one is that the resulting prototype filter is a global optimal solution. Compared with the traditional design method using general optimization methodology, the proposed method here is very simple and efficient. In addition, the stopband attenuation of the resulting FB is significantly higher than those offered by the traditional methods.

Random projection method for ultra wideband signal acquisition

Abstract High-speed high-resolution analog-to-digital (A/D) conversion demanded by ultra wideband (UWB) signal processing is a very challenging problem. This paper proposes a parallel random projection method for UWB signal acquisition. The proposed method can achieve high sampling rate, high resolution and technical feasibility of hardware implementation. In the proposed method, an analog UWB signal is projected over a set of random sign functions. Then the low-rate high-resolution analog-to-digital convertors (ADCs) are used to sample the projection coefficients. The signal can be reconstructed by simple linear calculation with the sampling matrix, without complying with optimization algorithm and prior knowledge. In other aspects, unlike other approaches that need to utilize an accurate time-shift at extremely high frequency, or design a hybrid filter bank, or generate specific basis functions or work for signals with prior knowledge, the proposed method is a universal sampling approach and easy to apply. The simulation results of signal to noise ratio (SNR) and spurious-free dynamic range (SFDR) validate the efficiency of the proposed method for UWB signal acquisition.

High-resolution ranging method based on low-rate parallel random sampling

In this paper, we propose a low-rate high-resolution ranging method for UWB (up to several GHz of sampling rate) ranging system. It exploits compressed sensing (CS) theory and a parallel sampling ADCs structure based on random projection (PSRP). To guarantee the effective application of CS on the received signal, we construct a dictionary in which the atoms are time-shifted versions of the transmitted signal. Hence the received signal can be low-rate sampled by PSRP. For an UWB ranging system using PSRP instead of the newly proposed analog-to-information converter, it possesses the universality of dictionary atoms, lower sampling rate and better performance for noisy signal. Additionally, since the dictionary size in this work can be adjusted flexibly, a desired high resolution can be achieved. The simulation results confirm these advantages via a noisy received signal (SNR=16 dB) which contains five target echoes. Though the received signal is sampled at less 10% of Nyquist rate, the probability of echo detection is over 95% and the distance resolution reaches the optimal of the conventional ranging method.