一种宽带信号数字下变频的实现方法

在宽带、超宽带应用中,单一信号带宽达几百兆赫兹;或者在不同中频同时调制多个信号产生的宽带信号也达数百兆赫兹,用常规的数字下变频方法很难实现。文章提出了一种基于DFT滤波器组的高效数字下变频结构,分析了该解调算法的特点和实现性能。对已知信号带宽和中频的宽带信号,对比了DFT滤波器组和多相分解算法的性能。对信号带宽和中频均在变化的信号,给出了实现思路。最后,给出了该DFT滤波器组的硬件实现方案。     

高效非均匀数字信道化及信号重建技术

针对宽带接收机接收信号多,且信号在频谱上呈现非均匀分布的情况,提出了基于多相离散傅里叶变换(DFT)滤波器组和信号重建的高效非均匀数字信道化的设计方法.该数字信道化结构由分析和综合两部分组成,采用同一组原型滤波器系数,通过对原型低通滤波器的优化设计提高其带外衰减性能,以利用平行结构正交镜像滤波器组重建信号.与常用的并行...     

基于立方卷积插值的信号DFT频谱校正算法

由于栅栏效应的存在,会使得基于信号DFT谱峰搜索的测频算法产生很大误差,因此在测频之前一般需对信号的DFT频谱进行校正。推导出用于单正弦信号DFT频谱校正的立方卷积插值核函数、插值函数及形状参数,并依据脉冲雷达信号是无数个正弦信号之和的事实,将其推广至脉冲雷达信号DFT频谱的幅度校正,给出其频谱检测算法。     

用于多路MCP-EBPSK信号解调的冲击滤波器组设计

修正的随机极性连续相位扩展的二元相移键控调制（MCP-EBPSK）通过随机化调制指数的符号,并加入功率谱调节系数,进一步降低了连续相位扩展的二元相移键控(CP-EBPSK)调制信号功率谱中的线谱分量,使得功率谱占用带宽更窄,信息传输更加的高效高速。多载波作为高频谱利用率的复用调制方式,与MCP-EBPSK结合势必会带来更高的系统性能,因此本文对用于解调单路MCP-EBPSK信号的冲击滤波器进行初步改进,通过添加陷波零点来抑制旁路干扰,设计出带陷波的冲击滤波器组。引入量子粒子群优化算法对加入陷波的冲击滤波器组进行优化得到滤波器组系数,仿真显示即使时频混叠的子载波间不满足正交关系,利用各冲击滤波器中心频率处极陡峭的陷波选频特性依然可以实现各子载波的正确解调。因此, 设计的冲击滤波器组可以用于子载波无保护间隔的多路MCP-EBPSK信号解调。      

余弦窗DFT递推算法

本文分析了DFT递推算法的窗谱特性及其对信号频谱精度的影响,给出了余弦窗DFT递推算法及其实现方法,介绍了算法的初始化方法及局部频域的频谱分析算法,分析了算法的复杂性进行了仿真分析。     

两通道正则正交的主分量滤波器组设计

本文研究了两通道正则正交的主分量滤波器组设计.给出了正则乘积滤波器的参数表示,设计转化成标准的LSIP问题并且提出了一种适合于单参数和双参数可行解迭代算法.     

脉间变频测量雷达正交误差的实时修正方法

针对脉间变频RCS测量雷达采用模拟正交解调方法获得同相分量和正交分量所引入的解调误差,提出了一种实时校准方法。该方法通过引入校准支路,将从测试信号耦合出的校准信号经固定延时和衰减后与回波信号在同一个脉冲周期内依先后顺序采集,由于校准支路信号只与系统内部状态有关而与测试目标和场地无关且间隔很短,可使用校准支路所得到的误差校准测试通道的信号。通过校准支路的应用可在系统整个工作时间内随时对解调误差进行修正。给出了校准支路的分析及设计,对使用模拟器测试的结果讨论了修正算法。     

DFT递归算法与实现研究

本文介绍了三种DFT算法:常系数乘法递归方式DFT算法,正向移动DFT算法、反向移动DFT算法,并进行了公式推导,导出了适于计算机运算的非常简便的递推公式,,同时对这三种DFT算法进行了比较和讨论,它们都可在频谱分析、功率谱估计,调制、解调和滤波中得到广泛应用,特别是两种移动DFT算法,它们的作用如同一个匹配滤波器,具有搜索、跟踪的能力,可在多路时间备择接收机中完成正交付载波分离和波特同步的双重功能。     

过采样广义调制滤波器组在B3G移动通信系统中的实现

本文在GMC-TDD-xDMA系统背景下从广义多载波并行传输的基本原理出发,讨论广义多载波调制解调的数字实现,得到多载波调制解调的广义DFT调制滤波器组实现结构,并给出了一种普遍适用的滤波器组快速实现方法.解决了DFT调制滤波器组在GMC-TDD-xDMA系统中运用时存在的问题.     

基于正交MFSK信号的解调优化算法

针对传统多进制频移信号解调算法存在计算量大、误码率高等问题,提出了一种基于正交多进制频移键控(Multiple Frequency Shift Keying,MFSK)信号的解调算法。该算法通过检测和判决MFSK信号在不同频率点处的功率谱峰值来完成信号同步,然后对信号的同向分量和正交分量进行反正切运算求得信号斜率,再根据信号斜率构建差值序列并建立MFSK信号解调数学模型,最后通过模型求解完成信号的调制进制识别和解调。该算法复杂度较低且仅呈线性增长,仿真结果表明该算法在性能上优于传统的小波解调算法,且当输入信噪比大于6 dB时,对2FSK、4FSK、8FSK和16FSK的解调正确率都可以达到90%以上。     

一种结合正弦参数提取和MDCT滤波器组的频谱优化方法

通过研究信号中正弦成分对改进的离散余弦变换(MDCT)的频谱产生的影响，针对使用MDCT滤波器组的音频编码系统，结合正弦参数提取，提出了一种对MDCT频谱进行优化的方法。这种方法利用MDCT和离散傅里里变换(DFT)之间的关系，在提取正弦参数的基础之上，通过简单线性变换求得MDCT谱，并在频域分离信号中的部分准静态正弦．从而达到优化MDCT频谱的目的。     

PR-QMF滤波器组在扩频通信中的应用

针对目前常见的FDMA、TDMA、CDMA,介绍了一种新的基于PR-QMF滤波器组的扩频技术.其扩频信号由合成滤波器产生,而分析滤波器则执行解扩过程.文章中简要介绍了该系统模型,并对其性能在AWGN及有正弦干扰情况下利用蒙特卡洛仿真,从而得出结论     

一种基于幅度积分的FSK非相干解调算法

FSK作为一种常用的调制方式,在小型化低功耗数字通信系统中被广泛应用,因此低复杂度的FSK数字解调算法成为研究重点。本文基于传统的功率检测算法,提出了一种基于幅度积分的FSK非相干解调算法（Amplitude-Integration Demodulation Algorithm, AIDA）。在AIDA算法中,接收信号先经过两个频点对应的带通滤波器,然后对滤波信号进行一个符号周期内的幅度积分,再对两个积分值进行相减,从而得到解调信号。由于采用了幅度积分的算法,复杂度被大大降低。仿真结果表明,AIDA可以改善FSK的解调性能。     

基于DFT滤波器组的宽带信号谱分析方法

本文利用DFT滤波器组、ZFFT,提出了一种宽带信号的实时谱分析方法。有效地解决了宽带信号高分辨率 谱分析要求的大运算量与实时性之间的矛盾。理论分析与计算机仿真表明该算法切实可行、有效并且易于实现。     

Design of M‐Channel IIR Uniform DFT Filter Banks Using Recursive Digital Filters

In this paper, we propose a method for designing a class of M‐channel, causal, stable, perfect reconstruction, infinite impulse response (IIR), and parallel uniform discrete Fourier transform (DFT) filter banks. It is based on a previously proposed structure by Martinez et al. [1] for IIR digital filter design for sampling rate reduction. The proposed filter bank has a modular structure and is therefore very well suited for VLSI implementation. Moreover, the current structure is more efficient in terms of computational complexity than the most general IIR DFT filter bank, and this results in a reduced computational complexity by more than 50% in both the critically sampled and oversampled cases. In the polyphase oversampled DFT filter bank case, we get flexible stop‐band attenuation, which is also taken care of in the proposed algorithm.     

Multiscale Wiener filter for the restoration of fractal signals:wavelet filter bank approach

A filter bank design based on orthonormal wavelets and equipped with a multiscale Wiener filter is proposed in this paper for signal restoration of 1/f family of fractal signals which are distorted by the transmission channel and corrupted by external noise. First, the fractal signal transmission process is transformed via the analysis filter bank into multiscale convolution subsystems in time-scale domain based on orthonormal wavelets. Some nonstationary properties, e.g., self-similarity, long-term dependency of fractal signals are attenuated in each subband by wavelet multiresolution decomposition so that the Wiener filter bank can be applied to estimate the multiscale input signals. Then the estimated multiscale input signals are synthesized to obtain the estimated input signal. Some simulation examples are given for testing the performance of the proposed algorithm. With this multiscale analysis/synthesis design via the technique of the wavelet filter bank, the multiscale Wiener filter can be applied to treat the signal restoration problem for nonstationary 1/f fractal signals     

On the design and realization of a class of uniform single rate FIR DFT filter banks

In this paper we present a computationally efficient realization of single rate uniform FIR filter banks for audio and spectral analysis applications. The channel filters in the analysis bank are represented as modulated versions of a prototype narrowband lowpass FIR filter. Using the IFIR filter design technique [23], [24], this prototype lowpass filter can be designed very efficiently as a cascade of two subfilters. The IFIR filter design is extended for the two-branch realization of uniform filter banks with overlapping channels. A generalized structure is presented which can be used for bothodd andeven stacking arrangements of the channels. The shaping filter structures for the two branches are realized from a single delay line and a single set of filter coefficients, thus conserving the total number of multipliers and delays in the overall realization. The postfilter structure, in conjunction with the Generalized DFT matrices, performs the channel selection. The Generalized DFT matrices are used to provide the necessary modulation for the postfilter coefficients so that the appropriate passbands are selected for each channel of the analysis bank. This leads to a polyphase network realization of the postfilter structure. We derive conditions so that the original input signal can be exactly reconstructed from the channel signals.This work was supported in part by the National Science Foundation under Grant MIP 85-08017 and in part by a University of California MICRO Grant with matching support from the Rockwell Corporation and the Intel Corporation.     

Partial spectrum reconstruction using digital filter banks

The problem of reconstructing a part of the spectrum is reduced to designing the filter bank to satisfy a set of conditions. For the case considered here, these conditions cannot be satisfied simultaneously, so perfect reconstruction is not possible. The necessary and sufficient conditions on the filters so that the resulting filter bank cancels most alias components are found. Such filter banks are called partial alias cancellation filter banks. The product of the polyphase transfer matrices of these filter banks must be a block pseudocirculant matrix. An algorithm design procedure is discussed, and examples are given to demonstrate the theory     

Time-varying discrete-time signal expansions as time-varying filter banks

The time-varying discrete-time signal expansion was analysed based on the theory of time-varying filter banks in detail. A general definition of time-varying discrete-time wavelet transforms is provided. Usually, a time-varying discrete-time signal expansion can be implemented using a time-varying filter bank. Using the time-varying filter bank theory, the authors developed a useful algorithm to calculate the dual basis function in a biorthogonal time-varying discrete-time signal expansion. Example is given to show the usage of the algorithm. In the last part, the authors provide a detailed analysis of the general time-varying discrete-time wavelet transform. Some useful properties of the time-varying discrete-time wavelet transform including their proofs are given. The relationship between the tree-structured implementation and the non-uniform filter bank implementation is discussed.