Research on fiber optic gyro signal de-noising based on wavelet packet soft-threshold

Gyro＇s drift is not only the main drift error which influences gyro＇s precision but also the primary factor that affects gyro＇s reliability. Reducing zero drift and random drift is a key problem to the output of a gyro signal. A three-layer de-nosing threshold algorithm is proposed based on the wavelet decomposition to dispose the signal which is collected from a running fiber optic gyro （FOG）. The coefficients are obtained from the three-layer wavelet packet decomposition. By setting the high frequency part which is greater than wavelet packet threshold as zero, then reconstructing the nodes which have been filtered out noise and interruption, the soft threshold function is constructed by the coefficients of the third nodes. Compared wavelet packet de-noise with forced de-noising method, the proposed method is more effective. Simulation results show that the random drift compensation is enhanced by 13.1%, and reduces zero drift by 0.052 6°/h.

A New Signal Processing Technique of π/4-DQPSK Modem Based on Software Radio

DQPSK modem has been chosen as the modem scheme in many mobile communication systems. A new signal processing technique of π/4-DQPSK modem based on software radio is discussed in this paper. Unlike many other software radio solutions to the subject, we choose a universal digital radio baseband processor operating as the co-processor of DSP. Only the core algorithms for signal processing are implemented with DSP. Thus the computation burden on DSP is reduced significantly. Compared with the traditional ones, the technique mentioned in this paper is more promising and attractive. It is extremely compact and power-efficient, which is often required by a mobile communication system. The implementation of baseband signal processing for π/4-DQPSK modem on this platform is illustrated in detail. Special emphases are laid on the architecture of the system and the algorithms used in the baseband signal processing. Finally, some experimental results are presented and the performances of the signal processing and compensation algorithms are evaluated through computer simulations.

Moving horizon based wavelet de-noising method of dual-observed geomagnetic signal for nonlinear high spin projectile roll positioning

Phase-frequency characte ristics of approximate sinusoidal geomagnetic signals can be used fo r projectile roll positioning and other high-precision trajectory correction applications.The sinusoidal geomagnetic signal deforms in the exposed and magnetically contaminated environment.In order to preciously recognize the roll information and effectively separate the noise component from the original geomagnetic sequence,based on the error source analysis,we propose a moving horizon based wavelet de-noising method for the dual-observed geomagnetic signal filtering where the captured rough roll frequency value provides reasonable wavelet decomposition and reconstruction level selection basis for sampled sequence;a moving horizon window guarantees real-time performance and non-cumulative calculation amount.The complete geomagnetic data in full ballistic range and three intercepted paragraphs are used for performance assessment.The positioning performance of the moving horizon wavelet de-noising method is compared with the band-pass filter.The results show that both noise reduction techniques improve the positioning accuracy while the wavelet de-noising method is always better than the band-pass filter.These results suggest that the proposed moving horizon based wavelet de-noising method of the dual-observed geomagnetic signal is more applicable for various launch conditions with better positioning performance.

Automatic de-noising and recognition algorithm for drilling fluid pulse signal

Wavelet forced de-noising algorithm is suitable for denoising of unsteady drilling fluid pulse signal, including baseline drift rectification and two-stage de-noising processing of frame synchronization signal and instruction signal. Two-stage de-noising processing can reduce the impact of baseline drift and determine automatic peak detection threshold range for signal recognition by distinguishing different features of frame synchronization pulse and instruction pulse. Rising and falling edge relative protruding threshold is defined for peak detection in signal recognition, which can make full use of the degree of the signal peak change and detect peaks flexibly with rising and falling edge relative protruding threshold combination. A synchronous decoding method was designed to reduce position uncertainty of the frame synchronization pulse and eliminate the accumulative error of time base drift, which determines the first instruction pulse position according to position of the frame synchronization pulse and decodes subsequent instruction pulse by taking current instruction pulse as new bit synchronization pulse. Special tool software was developed to tune algorithm parameters, which has a decoding success rate of about 95% for the universal coded signals. For the special coded signals with check byte, decoding success rate using the automatic threshold adjustment algorithm is as high as 99%.

Implementation of GPR Signals De-Noising Based on DSP

An important issue of ground-penetrating radar （GPR） signals analysis is de-noising thai is the guarantee of acquiring good detecting effect. The paper illustrates a successful application of digital single processor （DSP） based on wavelet shrinkage algorithm. In order to realize real-time GPP, signals analysis, some key issues are discussed such as the realization of fast wavelet transformation, the selection of CPU chip and the optimization of data movement. Experimenial results show that the DSP based application not only basically meets the real-time requirement of GPP, signals analysis, but also assures the quality of the GPR signals analysis.

A De-Noising Method for Track State Detection Signal Based on EMD

In the track irregularity detection, the acceleration signals of the inertial measurement unit (IMU) output which with low frequency components and noise, this paper studied a de-noising algorithm. Based on the criterion of consecutive mean square error, a de-noising method for IMU acceleration signals based on empirical mode decomposition (EMD) was proposed. This method can divide the intrinsic mode functions (IMFs) derived from EMD into signal dominant modes and noise dominant modes, then the modes reflecting the important structures of a signal were combined together to form partially reconstructed de-noised signal. Simulations were conducted for simulated signals and a real IMU acceleration signals using this method. Experimental results indicate that this method can efficiently and adaptively remove noise, and this method can better meet the precision requirement.

De-Noising of ECG Signals by Design of an Optimized Wavelet

In this paper, a different method for de-noising of ECG signals using wavelets is presented. In this strategy, we will try to design the best wavelet for de-nosing. Genetic algorithm tests wide range of quadrature filter banks and the best of them will be chosen that minimize the Signal-to-Noise Ratio (SNR). Furthermore, the wavelet function and scaling function related to these filters are reported as the best wavelet for de-noising. Simulation results for de-noising of a noisy ECG signal show that using obtained wavelet by proposed method improves the SNR of about 2.5 dB.

Research on Software Radio Fuze

The functions and characteristics of software radio are discussed. Using techniques and method of software radio, the concept and advantages of a new kind of radio fuze, software radio fuze, are analysed. Several kinds of hardware platform structures of the software radio fuze are studied and the key techniques are analysed. The software radio fuze will become the most promising radio fuze techniques in 21st century.

Adaptively Robust Phase Lock Loop for Low C/N Carrier Tracking in a GPS Software Receiver

在 GPS 应用程序的一个重要问题是怎么追踪 GPS (全球放系统) 在低 carrier-to-noise 比率(C/N ) 下面精确并且连续地发信号。在这份报纸，一个适应地柔韧的过滤器基于低 C/N 搬运人阶段锁循环(PLL ) 在一个 GPS 软件接收装置平台下面被开发。就传统的追踪循环上的低 C/N 搬运人信号的效果而言，追踪循环的平行关联被建立。一个线性最佳的评估者被设计在 kinematics 模型和大小处理依赖噪音。而且，一个适应地柔韧的过滤器基于三片断功能被设计调整因素。当收到的信号在有利条件下面时，新过滤器的表演很类似于一个标准 Kalman 过滤器。为追踪的一个实际弱搬运人，这新提高的 PLL 聪明地根据全部的阶段神经质分析调节循环参数。它成功地由适应地平衡更新的动态模型状态和大小的影响抵抗孤立点和动态模型错误。新过滤器的坚韧性和效率被测试实验的一些真实数据表明。结果证实有追踪循环的这个适应地柔韧的阶段的阶段错误的标准差能在 24 dB-Hz 附近与卫星 C/N 比率到达 0.01 个周期，它显著地改进表演。

A NEW DE-NOISING METHOD BASED ON 3-BAND WAVELET AND NONPARAMETRIC ADAPTIVE ESTIMATION

Wavelet de-noising has been well known as an important method of signal de-noising. Recently,most of the research efforts about wavelet de-noising focus on how to select the threshold,where Donoho method is applied widely. Compared with traditional 2-band wavelet,3-band wavelet has advantages in many aspects. According to this theory,an adaptive signal de-noising method in 3-band wavelet domain based on nonparametric adaptive estimation is proposed. The experimental results show that in 3-band wavelet domain,the proposed method represents better characteristics than Donoho method in protecting detail and improving the signal-to-noise ratio of reconstruction signal.

Coefficients de-noising with wavelet transform for magnetic flux leakage data obtained from oil pipeline

This paper considers the problem of noise cancellation for the magnetic flux leakage (MFL) data obtained from the inspection of oil pipelines. MFL data is contaminated by various sources of noise, and the noise can considerably reduce the detectability of flaw signals in MFL data. This paper presents a new de-noising approach for removing the system noise contained in the MFL data by using the coefficients de-noising with wavelet transform. Experimental results are presented to demonstrate the advantages of this de-noising approach over the conventional wavelet de-noising method.

Improved Circular Correlation Methods for Acquisition in Software GPS Receiver

In this paper the authors explore the Global Positioning System （GPS） signal acquisition and tracking algorithms used in software GPS receiver. Acquisition time is the most important parameter in evaluating the performance of a software GPS receiver in terms of its speed. A trade-off study is done to seek a good balance between the acquisition accuracy and the processing time. The frequency-domain acquisition method by circular correlation, used in a software GPS receiver, has been improved by studying the power spectrum of the Coarse Acquisition （C/A） code alone. The analysis of C/A code reveals that its power spectrum is symmetrical; hence only half the points are required to perform circular correlation. Besides, either half of the spectrum is asymmetrical where a larger amount of power is concentrated in almost one-quarter of the spectrum on its either sides. This further reduces the number of points used to perform correlation. Comparative results of MATLAB simulation of full-size, half-size and quarter-size circular correlation done on actual data stored on hard disk are provided, and they agree with those obtained using GPS receiver. Further reduction in acquisition time has been achieved by investigating the effect of length of the noncoherent pre-integration period. The improved acquisition methods pave way for further development of new algorithms to enhance software GPS receiver performance.

STABLE RECOVERY OF SPARSELY CORRUPTED SIGNALS THROUGH JUSTICE PURSUIT DE-NOISING

This paper considers a corrupted compressed sensing problem and is devoted to recover signals that are approximately sparse in some general dictionary but corrupted by a combination of interference having a sparse representation in a second general dictionary and measurement noise.We provide new restricted isometry property(RIP)analysis to achieve stable recovery of sparsely corrupted signals through Justice Pursuit De-Noising(JPDN)with an additional parameter.Our main tool is to adapt a crucial sparse decomposition technique to the analysis of the Justice Pursuit method.The proposed RIP condition improves the existing representative results.Numerical simulations are provided to verify the reliability of the JPDN model.

Characteristics of acoustic emission signals in damp cracking coal rocks

A uniaxial load experiment on coal rocks at different stress rates was carried out, based on the characteristics of acoustic emission (AE) signals in cracking coal rocks, decomposition, de-noising and reconstruction for the AE signals through wavelet packet transform for solving the current problems created by the presence of noise in AE signals and the existing problems in AE signal processing. The results show that the various characteristics of AE signals in coal rocks cracking under different situations can be clearly reflected, after the AE signals are de-noised by the wavelet packet. Compared to dry coal rocks, the number of AE occurrences in damp coal rocks was significantly reduced, as well as the average amplitude. The number of AE occurrences in damp and dry coal rocks clearly increased with increases in the loading rate, but the largest amplitude of the AE signals in damp coal rocks has been reduced. There is no clear evidence of change in dry coal rocks.

Development of a signal collecting system for double-channel auscultation

As is known to all, many auscultations of human body, such as heart, lung and carotid artery sound, play a major role in clinic. And their signal frequency is in the range that computer sound card can handle, so we can use analog-to-digital (A/D) conversion of sound card as A/D conversion (ADC) of auscultation signals, and double-channel auscultation signals (DCASs) can be input into personal computer(PC) by sound card that every computer has, and it makes the hardware design more simple. Because auscultation signals are input from sound card, any common music processing software (CMPS) can be used to process received auscultative signals, and it is not necessary to write special processing software for them. Therefore, only a double-channel and front-end analog signal processing circuit of auscultation is needed to be designed. By this method of constituting the signal collecting system for double-channel auscultation, it is simple and low cost, and needs no special software, so it has very important values and a broad market prospect.

EEGbands: A Computer Program to Statistically Analyze Parameters of Electroencephalographic Signals

The quantitative analysis of electroencephalographic activity (EEG) is a useful tool for the study of changes in brain electrical activity during cognitive and behavioral functions in several experimental conditions. Their recording and analysis are currently carried out primarily through the use of computer programs. This paper presents a computerized program (EEGbands) created for Windows operating systems using the Delphi language, and designed to analyze EEG signals and facilitate their quantitative exploration. EEGbands applies Rapid Fourier Transformation to the EEG signals of one or more groups of subjects to obtain absolute and relative power spectra. It also calculates both interhemispheric and intrahemispheric correlation and coherence spectra and, finally, applies parametrical statistical analysis to these spectral parameters calculated for wide frequency EEG bands. Unlike other programs, EEGbands is simple and inexpensive, and rapidly and precisely generates results files with the corresponding statistical significances. The efficacy and versatility of EEGbands allow it to be easily adapted to different experimental and clinical needs.

数字信号处理课程实验教学平台建设

探索数字信号处理课程的实验教学平台建设,提出了三种实验教学平台建设方案。基于MATLAB软件的实验教学平台和基于CCS软件的实验教学平台,按照实验教学内容,在MATLAB软件平台上编写MATLAB脚本实验程序,在CCS软件平台上编写C语言实验程序,组成实验教学程序库,参考该程序库完成实验教学。基于MATLAB软件和DSP实验箱的实验教学平台,结合实验教学内容,编写MATLAB脚本程序和C语言程序,组成实验教学程序库完成实验教学。借助三种实验教学平台,以FFT快速算法和FIR带阻滤波器设计及其滤波分析为例,讨论了其实验方案及其步骤,比较实验结果,可以看出,三种实验平台都能较好地完成数字信号处理课程的实验教学。

沥青混合料摊铺机熨平板频率振动测试系统研究

通过对摊铺机与混合料相互作用理论研究可知,存在高效的振动频率范围,在此范围内沥青混合料容易被振实,沥青混合料获得较高的初压密实度。然而在实际施工中,摊铺机并没有频率测定的专用仪器,摊铺机通常采用档位或者百分比的方式调节振捣和振动频率,无法判断振动频率是否在与材料相适应的频率范围内,施工过程中的调节具有较大的盲目性。本文研究提出的摊铺机多频率振动监测系统,可以对摊铺机的振动频率进行实时监测,对施工过程进行指导,保证摊铺机高效工作。

基于云端软件定义水声的跨域通信系统

由于水声通信性能的制约,跨水-空界面的数据传输性能难以进一步提升。针对该问题,文中提出了一种基于云端软件定义水声(C-SDA)的跨域通信系统架构。C-SDA将水声接收机从水面中继节点移动到云端(即监测中心),并利用无线电通信带宽交换云端计算资源进行水声信号解调和解码。中继网关的水声-无线电双栈网络协议被简化为单栈结构,避免了数据包的封装和再封装,节省了硬件成本。C-SDA不仅能实现先进的通信信号处理,而且能促进水声通信技术的更新和迭代。现场测试实验结果表明,与自研的嵌入式水声接收机相比,C-SDA能够适用更高性能的均衡器,使误码率得到显著改善。

面向飞腾迈创DSP的自主软件栈设计

飞腾迈创DSP是国防科技大学计算机学院为了突破卡脖子技术,解决我国相关重点领域内芯片长久受制于人的现实问题而自主设计的高性能数字信号处理器。由于该系列芯片采用全自主设计的指令集,无法兼容已有的软件,一套自主完备且高效的软件栈是决定飞腾迈创DSP生命力的关键。基于团队长期以来的持续工作,系统阐述了飞腾迈创DSP软件栈的设计原则与层次化架构,重点介绍了包括支持层、编译层以及工具层在内的相关软件工具的创新功能、实现方法以及性能。同时,结合用户的反馈与团队的思考,还讨论了飞腾迈创DSP软件栈未来需要探索的相关问题。