New nonlinear algorithms for narrowband interference suppression inCDMA spread-spectrum systems

The narrow-band interference suppression capability of spread-spectrum systems can be further enhanced by employing interference suppression filters. This paper proposes a number of new nonlinear algorithms for narrow-band interference suppression in code division multiple access spread-spectrum systems. Our research consists of two parts. (1) We propose a multiuser decision-directed Kalman (MDK) filter, which has the same performance as the nonlinear approximate conditional mean (ACM) filter but a much simpler algorithm. (2) We use the nonlinear function in the ACM and the MDK filters to develop nonlinear adaptive least mean square filters with significantly improved performance. Simulation results indicate that our nonlinear algorithms outperform conventional linear ones     

New nonlinear algorithms for estimating and suppressing narrowbandinterference in DS spread spectrum systems

It has been shown that the narrowband (NB) interference suppression capability of a direct-sequence (DS) spread spectrum system can be enhanced considerably by processing the received signal via a prediction error filter. The conventional approach to this problem makes use of a linear filter. However, the binary DS signal, that acts as noise in the prediction process, is highly non-Gaussian. Thus, linear filtering is not optimal. Vijayan and Poor (1990) first proposed using a nonlinear approximate conditional mean (ACM) filter of the Masreliez (1975) type and obtained significant results. This paper proposes a number of new nonlinear algorithms. Our work consists of three parts. (1) We develop a decision-directed Kalman (DDK) filter, that has the same performance as the ACM filter but a simpler structure. (2) Using the nonlinear function in the ACM and the DDK filters, we develop other nonlinear least mean square (LMS) filters with improved performance. (3) We further use the nonlinear functions to develop nonlinear recursive least squares (RLS) filters that can be used independently as predictors or as interference identifiers so that the ACM or the DDK filter can be applied. Simulations show that our nonlinear algorithms outperform conventional ones     

Rejection of multiple tone interference in DS spread-spectrumsystems employing minimum redundant transversal filters

A direct-sequence spread-spectrum (DSSS) receiver using a new transversal filter structure called minimum redundant transversal filter (MRTF), for combating narrow-band interference is proposed. The signal-to-noise (SNR) ratio improvement factors are derived under the conditions of multiple tone interference. The effectiveness of the new suppression filter is examined and the results obtained reveal the fact that the MRTF structure leads to superior performance especially when the frequencies of the jamming tones are near the carrier frequency of the modulated signal     

Narrow-band interference suppression in spread-spectrum CDMAcommunications using pipelined recurrent neural networks

This paper investigates the application of pipelined recurrent neural networks (PRNN's) to the narrow-band interference (NBI) suppression over spread-spectrum (SS) code-division multiple-access (CDMA) channels in the presence of additive white Gaussian noise (AWGN) plus non-Gaussian observation noise. Optimal detectors and receivers for such channels are no longer linear. A PRNN that consists of a number of simpler small-scale recurrent neural network (RNN) modules with less computational complexity is conducted to introduce best nonlinear approximation capability into the minimum mean-squared error nonlinear predictor model in order to accurately predict the NBI signal based on adaptive learning for each module from previous non-Gaussian observations. Once the prediction of the NBI signal is obtained, a resulting signal is computed by subtracting the estimate from the received signal. Thus, the effect of the NBI can be reduced. Moreover, since those modules of a PRNN can be performed simultaneously in a pipelined parallelism fashion, this would lead to a significant improvement in its total computational efficiency. Simulation results show that PRNN-based NBI rejection provides a superior signal-to-noise ratio (SNR) improvement relative to the conventional adaptive nonlinear approximate conditional mean (ACM) filters, especially when the channel statistics and exact number of CDMA users are not known to those receivers     

一种直扩通信窄带干扰抑制的自适应滤波技术

文中研究了自适应非线性滤波在直扩通信中抑制窄带干扰的应用,采用修正LMS(MLMS)自适应滤波算法对窄带干扰进行抑制,并运用ACM滤波非线性函数进行非线性处理,使滤波性能明显改善.最后用MATLAB仿真自适应滤波过程,验证了算法的滤波性能.     

微弱信号非线性检测在随钻电磁波中的应用

在随钻电磁波测井工程中, 随着勘探深度加深, 信号呈现越来越微弱的特性, 有效提取强噪声背景下的微弱电磁波信号对于指导随钻工程勘探具有重要的意义.传统的滤波方法仅滤除带外噪声, 带内噪声不能被很好解决, 针对此问题, 文章设计带外硬件滤波电路和带内基于最小均方算法的可变参数自适应谱线增强(adaptive line enhancer, ALE)算法来构造组合滤波算法.理论分析和仿真研究表明:该组合算法能够提高高动态、低信噪比的微弱电磁波有用信号的估计精度, 有效提高信噪比和抑制工程环境噪声的能力.该组合算法在滤除带外噪声的基础上, 对于带内高斯白噪声抑制能力提高约10 dB, 进一步解决了实际工程问题.     

On the use of a suppression filter for CDMA overlay

This paper is concerned with a direct-sequence code-division multiple-access (DS-CDMA) system operating over a Rayleigh fading channel and sharing a common spectrum with a narrow-band waveform. A suppression filter at the receiver is employed to reduce the narrow-band interference. We evaluate the average up-link bit error rate (BER) performance and investigate how the performance is influenced by various parameters, such as the number of taps of the suppression filter, the number of multiple-access users, the ratio of narrow-band interference bandwidth to the spread-spectrum bandwidth, the interference power to signal power ratio, the ratio of the offset of the interference carrier frequency from the spread-spectrum carrier frequency to the half spread-spectrum signal bandwidth, and so on     

Wavelet Notch Filter Design of Spread-Spectrum Communication Systems for High-Precision Wireless Positioning

Spread-spectrum communication systems are now commonly used in the field of cellular telephone positioning. However, wireless positioning systems by low-power spread-spectrum communication are extremely vulnerable to high-power interference, which limits achievable measurement precision. In this paper, a bandwidth variable wavelet notch filter design method is proposed to suppress a large number of jammers in multiple locations with noise interfering with spread-spectrum systems. The filter uses combinations of Gaussian wavelets with optimal time-frequency localization and computational efficiency for real-time operation of denoising. The performance of the adaptive filter has been evaluated by experiments associated with a spread-spectrum communication system model employing a reliable noise detector to locate the filter notch. Experimental results demonstrate that the proposed wavelet notch filter removes the narrow-band interference in accordance with the corrupted frequency contents while minimizing signal distortion and information loss, which leads to high-precision wireless positioning.     

Recursive estimation of images using non-Gaussian autoregressivemodels

We consider recursive estimation of images modeled by non-Gaussian autoregressive (AR) models and corrupted by spatially white Gaussian noise. The goal is to find a recursive algorithm to compute a near minimum mean square error (MMSE) estimate of each pixel of the scene using a fixed lookahead of D rows and D columns of the observations. Our method is based on a simple approximation that makes possible the development of a useful suboptimal nonlinear estimator. The algorithm is first developed for a non-Gaussian AR time-series and then generalized to two dimensions. In the process, we draw on the well-known reduced update Kalman filter (KF) technique of Woods and Radewan (1977) to circumvent computational load problems. Several examples demonstrate the non-Gaussian nature of residuals for AR image models and that our algorithm compares favorably with the Kalman filtering techniques in such cases.     

Analysis of DFT-based frequency excision algorithms fordirect-sequence spread-spectrum communications

The capacity of direct-sequence spread-spectrum modulation to reject narrow-band interference can be significantly improved by eliminating narrow-band energy at the receiver in a process called frequency excision. This paper considers several algorithms that operate on the real-time discrete Fourier transform (DFT) of the received signal to perform frequency excision. The case in which only the signal and additive white Gaussian noise (AWGN) are present at the receiver is considered as a means of comparing the relative performance of different algorithms that operate without knowledge of the power spectral density of the interference. An approach for analysis, using the postcorrelation signal-to-noise ratio (SNR) as the figure of merit, is presented that is valid for a broad class of spreading modulations. First, the algorithm that sets a fixed fraction of the frequency domain record to zero is examined using rank-order statistics as an analytical tool. This result is then generalized to confirm previous estimates of SNR degradation for the algorithm that sets all values that exceed a threshold to zero. These results are again generalized to apply to the algorithm that sets a fixed fraction of the band to a fixed amplitude while retaining phase information in an algorithm called fraction clip. The relative performances of several clip algorithm options are derived as special cases. Finally, a performance measure of the algorithms in the presence of multiple narrow-band interference is provided and illustrated with an example     

The efficiency of ultrawideband detection of target with unknown range and speed in the presence of narrow-band interference

The impact of Gaussian narrow-band interference on characteristics of the receiver synthesized for target detection in the presence of the Gaussian white noise was investigated. The possibility of interference suppression by applying a rejection filter was also considered.     

EM-based recursive estimation of channel parameters

Recursive (online) expectation-maximization (EM) algorithm along with stochastic approximation is employed in this paper to estimate unknown time-invariant/variant parameters. The impulse response of a linear system (channel) is modeled as an unknown deterministic vector/process and as a Gaussian vector/process with unknown stochastic characteristics. Using these models which are embedded in white or colored Gaussian noise, different types of recursive least squares (RLS), Kalman filtering and smoothing and combined RLS and Kalman-type algorithms are derived directly from the recursive EM algorithm. The estimation of unknown parameters also generates new recursive algorithms for situations, such as additive colored noise modeled by an autoregressive process. The recursive EM algorithm is shown as a powerful tool which unifies the derivations of many adaptive estimation methods     

基于自适应IIR陷波滤波器的窄带干扰抑制技术

在存在窄带干扰时，扩频通信系统的性能可以通过使用各种不同的抗干扰滤波器来进一步提高。文中研究了二阶自适应格型IIR陷波滤波器在直扩通信中抗窄带干扰的应用，推导了系统信噪比改善因子和误比特率的闭合表达式。计算机仿真表明了该分析结果的正确性。     

Performance Analysis of Narrow-Band Interference Rejection Techniques in DS Spread-Spectrum Systems

Linear least squares estimation (LLSE) techniques can provide an effective means of suppressing narrow-band interference in direct sequence (DS) spread-spectrum systems. In the results presented here, analytical expressions for bit error rate are derived for two DS spread-spectrum systems under the conditions of either tone or narrowband Gaussian interference. It is shown that the most common LLSE filter design can lead to performance inferior to that of various other filter designs. However, results are also presented demonstrating that an LLSE filter design motivated by the structure of the maximum-likelihood receiver leads to consistently superior performance. The performance of a system using this new design criterion is compared with that of an approximation to the maximum-likelihood (ML) receiver for the tone interference model and with that of the exact ML receiver for the Gaussian interference. Finally, it is shown that the bit error rate estimate obtained from application of a Gaussian approximation for the test statistic is overly pessimistic for the systems studied here.     

扩频系统中自适应窄带干扰抑制滤波器对PN码捕获性能的影响

本文通过详细的理论推导,分析了扩频系统中自适应窄带干扰抑制滤波器对PN码捕获性能的影响;并根据滤波器理论,给出了自适应窄带干扰抑制滤波器的幅频响应、群延迟响应和相应的仿真结果.理论分析与仿真结果表明,自适应干扰抑制滤波器在抑制窄带干扰的同时,也抑制了部分扩频信号,从而形成较大的相关旁瓣,对PN码捕获性能产生严重的影响.     

Adaptive lattice filters for CDMA overlay

This paper presents the behavior of reflection coefficients of a stochastic gradient lattice (SGL) filter applied to a code division multiple-access overlay system. Analytic expressions for coefficients for a two-stage filter are derived in a Rayleigh fading channel with the presence of narrow-band interference and additive white Gaussian noise. It is shown that the coefficients of the lattice filter exhibit separate tracking and convergent properties, and that compared to an LMS filter, the lattice filter provides fast rate of convergence, while having good capability of narrow-hand interference suppression     

Suppression of Narrow-Band Interference in a PN Spread-Spectrum Receiver Using a CTD-Based Adaptive Filter

Analytical results have shown that adaptive filtering can be a powerful tool for the rejection of narrow-band interference in a spreadspectrum receiver. However, the complexity of adaptive filtering hardware has hindered the experimental verification of these results. This paper describes a new adaptive filter architecture for implementing the Widrow-Hoff LMS algorithm while using only two multipliers regardless of filter order. This hardware simplification is achieved through the use of a burst processing technique. A 16-tap version of this adaptive filter constructed using charge-transfer devices (CTD's) is used to suppress a single tone jammer in a direct sequence spread-spectrum receiver. Probability of error measurements demonstrating the effectiveness of the adaptive filter for suppressing the single tone jammer along with simulation results for the optimal Weiner-Hopf filter are presented and discussed.     

A GLRT-based spread-spectrum receiver for joint channel estimationand interference suppression

The author considers the problem of demodulating a direct-sequence (DS) spread-spectrum signal in the presence of narrowband interference and multipath. A receiver is considered that is based on the generalized likelihood-ratio test (GLRT), in which the interferer is modeled as an Nth-order circular Gaussian autoregressive (AR) process and the multipath channel is represented by a tapped-delay line. The maximum-likelihood joint estimator for the channel coefficients and interferer AR parameters is then derived. Analytical expressions for bit-error rate are presented for GLRT receiver, under the assumption of perfect estimates of the channel and interferer parameters. The performance of the GLRT receiver is compared to that of a DS receiver using a transversal equalizer. It is shown that the GLRT receiver consistently outperforms the equalizer-based receiver by 2-3 dB. The performance of an adaptive GLRT receiver is evaluated where the recursive least-squares algorithm is used to jointly estimate the interferer and channel parameters     

自适应滤波算法在微弱振动测量中的应用

将递归最小二乘自适应滤波算法应用于激光多普勒测振技术中,搭建了相应的微弱振动测量装置。模拟仿真与实验中,通过与设计的切比雪夫低通滤波算法对比,结果表明:该递归最小二乘自适应滤波算法能够有效抑制随机高斯白噪声,还原出原始信号;能够对简谐振动信号实现有效滤波,并且可以还原出淹没在噪声中的低频20 Hz信号;文中算法可以去除语音噪声,使声音更加纯净,增强语音信号,以此验证了该算法在外差振动测量中的可行性。该算法简单易用、收敛性强、速度快,尤其对于随机噪声的去除比普通的低通滤波器更加有效。     

Performance of DS Spread-Spectrum Receiver Employing Interference-Suppression Filters Under a Worst-Case Jamming Condition

In this paper, the worst-case power spectral density of a narrow-band Gaussian jammer operating in a direct sequence (DS) spread-spectrum system employing an interference-rejection filter is derived under a joint power and bandwidth constraint on the jammer. The effectiveness of the suppression filter under these conditions is examined and average probability of error results for the system's performance are presented.