2016 New Trends in Signal Processing (NTSP)最新文献

Computation and evaluation allan variance results 计算和评估阿伦方差结果

2016 New Trends in Signal Processing (NTSP) Pub Date : 2016-10-01 DOI: 10.1109/NTSP.2016.7747786

Miroslav Matejček, M. Šostronek

{"title":"Computation and evaluation allan variance results","authors":"Miroslav Matejček, M. Šostronek","doi":"10.1109/NTSP.2016.7747786","DOIUrl":"https://doi.org/10.1109/NTSP.2016.7747786","url":null,"abstract":"This article deals with Allan variance as useful method for noise performance evaluation of inertial sensors which are used in inertial measurement unit (IMU) and different guidance systems. The noise component of inertial sensors is important part from group of inertial sensors errors, which determines accuracy of inertial navigation systems in real time. Because inertial measurement unit consists from accelerometers and gyroscopes, all sensor errors influence the position determination accuracy. Trajectory length is estimated from double integral of measured acceleration, therefore the error of length trajectory determination is increased rapidly. Gyroscope errors influence measured direction of movement. Knowledge of inertial sensor errors and their changes in time is necessary to increase the inertial navigation accuracy. Inertial sensor stochastic errors could be estimated in time or frequency domain. Allan method is based on the computation of root mean square random drift error as a function of average time [1], [2]. Allan variance (AVAR) could be computed in different way as, nonoverlapped AVAR, not fully overlapping AVAR, fully overlapping AVAR, total variance and modified total variance [1]. Main part of this article deals with design of simplified AVAR computation and simplified AVAR computation performances are evaluated.","PeriodicalId":232837,"journal":{"name":"2016 New Trends in Signal Processing (NTSP)","volume":"20 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126651481","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 8

Analysis and decoding of radio signals for remote control of drones 用于遥控无人机的无线电信号分析与解码

2016 New Trends in Signal Processing (NTSP) Pub Date : 2016-10-01 DOI: 10.1109/NTSP.2016.7747781

Michal Haluza, J. Cechak

引用次数: 14

Hilbert-huang transform and its application in seismic signal processing Hilbert-huang变换及其在地震信号处理中的应用

2016 New Trends in Signal Processing (NTSP) Pub Date : 2016-10-01 DOI: 10.1109/NTSP.2016.7747776

R. Berešík

{"title":"Hilbert-huang transform and its application in seismic signal processing","authors":"R. Berešík","doi":"10.1109/NTSP.2016.7747776","DOIUrl":"https://doi.org/10.1109/NTSP.2016.7747776","url":null,"abstract":"The detection of targets in military and security applications involves the usage of sensor systems which consist of a variety of sensors such as seismic, acoustic, magnetic and image ones as well. In order to extract signal features, which characterize particular targets, using of appropriate signal processing algorithms is required. Seismic signals can be considered as nonstationary and nonlinear signals especially in near-field seismic zone. Most of the signal processing algorithms assumed that signals are linear and stationary. However, in many cases this assumption is not valid, especially in case of seismic signals generated by moving vehicles, walking persons or gunfire activity. There are several methods which can be used for seismic signal processing, like short-time Fourier transform (STFT), Wavelet transform (WT) and Wigner-Ville distribution (WVD). The paper presents the concept of the seismic sensor system based on Micro-Electro-Mechanical-System (MEMS) sensor SF1500S. A dedicated to vehicle detection. The main part of the paper deals with application of the Hilbert-Huang transform (HHT) to seismic signal processing in time and time-frequency domain. In conclusion, the outcomes of experiments provide comparison of HHT and STFT efficiency in terms of seismic features description of moving vehicle.","PeriodicalId":232837,"journal":{"name":"2016 New Trends in Signal Processing (NTSP)","volume":"18 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123635627","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 7

Synchronization of two tree parity machines 两个树奇偶校验机的同步

2016 New Trends in Signal Processing (NTSP) Pub Date : 2016-10-01 DOI: 10.1109/NTSP.2016.7747782

Martin Javurek, M. Turčaník

引用次数: 6

Possibility of usage the latest GSM generations for the purpose of UAV communication 为无人机通信的目的使用最新一代GSM的可能性

2016 New Trends in Signal Processing (NTSP) Pub Date : 2016-10-01 DOI: 10.1109/NTSP.2016.7747794

Tomáš Volčko, V. Moucha, P. Lipovský, K. Draganová

引用次数: 11

Modified LEACH protocol for heterogeneous wireless networks 改进的异构无线网络LEACH协议

2016 New Trends in Signal Processing (NTSP) Pub Date : 2016-10-01 DOI: 10.1109/NTSP.2016.7747774

Amr Amwary, D. Maga, T. Nahdi

引用次数: 16

Correlation-based TDOA algorithm for the target localization at low signal to noise ratio 基于相关性的低信噪比TDOA算法的目标定位

2016 New Trends in Signal Processing (NTSP) Pub Date : 2016-10-01 DOI: 10.1109/NTSP.2016.7747787

Z. Matousek, M. Babjak, J. Ochodnicky

引用次数: 6

FPGA-based system level design of control systems: A case study of three-axis positioning controller implementation 基于fpga的控制系统级设计:以三轴定位控制器实现为例

2016 New Trends in Signal Processing (NTSP) Pub Date : 2016-10-01 DOI: 10.1109/NTSP.2016.7747790

M. Stankovic, Stojadin M. Manojlovic, Slobodan M. Simic, Srdjan T. Mitrović, M. Naumovic

引用次数: 2

UHF/C-band testing of AOA estimation using MUSIC algorithm MUSIC算法在UHF/ c波段的AOA估计测试

2016 New Trends in Signal Processing (NTSP) Pub Date : 2016-10-01 DOI: 10.1109/NTSP.2016.7747792

Xuan Luong Tran, J. Veselý, Sang Van Doan, P. Hubáček

{"title":"UHF/C-band testing of AOA estimation using MUSIC algorithm","authors":"Xuan Luong Tran, J. Veselý, Sang Van Doan, P. Hubáček","doi":"10.1109/NTSP.2016.7747792","DOIUrl":"https://doi.org/10.1109/NTSP.2016.7747792","url":null,"abstract":"This paper presented a study of direction of arrival estimation using multiple signal classification algorithm on two frequency bands (UHF-band and C-band). The used algorithm in the paper is one of the superresolution direction of arrival estimation algorithms and it was simulated to analyze the effects of various parameters on the direction of arrival accuracy and resolution. Then, the measuring workplace was established to verify the results of the simulation. In the practical measurement, two 4-element uniform linear arrays were used to estimate the direction of arrival of the noncoherent signal sources for the different frequency bands. The measured signals were processed in the Matlab using multiple signal classification algorithm for direction of arrival estimation. The measurement system estimated the direction of arrival of the signal in the UHF-band with accuracy around 4° and resolution around 10°. In the C-band, the accuracy and resolution of direction of arrival estimation were around 3° and 10° respectively. In comparison, the measurement results were a bit different from the simulation due to environment condition of measuring workplace.","PeriodicalId":232837,"journal":{"name":"2016 New Trends in Signal Processing (NTSP)","volume":"67 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2016-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134641072","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 1

Stability testing of hybrid DT+CT systems DT+CT混合系统稳定性测试

2016 New Trends in Signal Processing (NTSP) Pub Date : 2016-10-01 DOI: 10.1109/NTSP.2016.7747777

D. Biolek, Z. Kolka, V. Biolková

引用次数: 1