Direction of Arrivals Estimation for Correlated Broadband Radio Signals by MVDR Algorithm Using Wavelet

A theoretical relationship between the wavelet transform and the fast fourier transformation(FFT) methods in broadband wireless signal is proposed for solving the direction of arrivals(DOAs) estimation problem. This leads naturally to the derivation of minimum variance distortionless response(MVDR) algorithm, which combines the benefits of subspace methods with those of wavelet, and spatially smoothed versions are utilized which exhibits good performance against correlated signals. We test the method's performance by simulating and comparing the performance of proposed algorithm, FFT MVDR and MVDR with correlated signals, and an improved performance is obtained.

Redshift Anomaly of the 2292 MHz Radio Signal Emitted by the Pioneer-6 Space Probe as Multiple Interactions with Photo-Ionized Electrons in the Solar Corona

This paper calculates the redshift of the 2292 MHz radio photon emitted by the Pioneer-6 space probe. The signal crossed the solar corona on the days close to the solar occultation between November and December 1968, the only ones for which scientific data are available, until it reached a terrestrial radio receiver. The specific study is based on a calculated orbital model of the Earth and Pioneer-6 system made on a scale of 1:100,000 by a CAD, on the New Tired Light theory adapted to the geometric and physical configuration of the topic and on a computational method. Removing the Doppler shift contributions of proper and rotational motions, due to the set-up of the receiver, and excluding the recombination factor of neutral hydrogen, which is irrelevant for distances within 1 AU, the calculation of the redshift can be traced back to the interactions between the radio signal and the electrons of the solar corona alone. The latter are contained in a Stroemgren sphere and photo-ionized by solar radiation in the UV and X-ray range. Furthermore, in order to have an interactional redshift contribution, the electrons have to satisfy the Wigner-Crystal Precondition for which their unitary potential energy is greater than their kinetic energy. Otherwise, a Thomson scattering process takes place in which the energy of the radio photon remains unchanged. The comparison between the gravitational redshift together with the interactional redshift detected from this study methodology and the total redshift obtained from other scientific studies shows a similarity between the curves, including the observational data, both in terms of values, trend of the graphs and single punctual variations.

Anomalies Observed in VLF and LF Radio Signals on the Occasion of the Western Turkey Earthquake(M_(W)=5.7)on May 19,2011

Since 2009 a network of VLF (20 - 60 kHz) and LF (150 - 300 kHz) radio receivers is operating in Europe in order to study the disturbances produced by the earthquakes on the propagation of these signals. In 2011 the network was formed by nine receivers, of which three are located in Italy and one is in Austria, Greece, Portugal, Romania, Russia and Turkey. On May 19, 2001 an earthquake (Mw = 5.7) occurred in western Turkey, that is inside the “sensitive” area of the network. The radio data collected during April-May 2011 were studied using the Wavelet spectra, the Principal Component Analysis and the Standard Deviation trends as different methods of analysis. Evident anomalies were revealed both in the signals broadcasted by the TRT transmitter (180 kHz) located near Ankara and in a VLF signal coming from a transmitter located in Western Europe and collected by the receiver TUR of the network located in eastern Turkey. Evident precursor phases were pointed out. Some differences in the efficiency of the three analysis methods were revealed.

Variations of VLF radio signals and atmospherics during the deep earthquake with M = 8.2 occurred on 24 May 2013 near Kamchatka peninsula

To detect seismic disturbances in the lower ionosphere, we have used the signals of very-lowfrequency radio transmitters and natural radio signals—electromagnetic emission of lightning discharges—atmospherics. On earlier results of observation of atmospherics, it was obtained that the earthquake effects are displayed as weight-hourly amplitude increases on the day of event or within 3 days after them. Possible earthquake precursors are also manifested as one-day (within one to several hours) increases in the amplitude of atmospherics on average 5 - 12 days before the event. Analysis shows that seismic effects in the amplitude of atmospherics have been observed in the case of sufficiently strong (magnitude M > 4.5) and not very deep (usually no deeper than 50 km) earthquakes. The effects of the events of the earthquake with magnitude of 8.2 occurring in the Sea of Okhotsk on 24.05.13 not far from the Kamchatka Peninsula at a depth of 609 km considered in this work have shown that even deep earthquakes may have precursors in the form of disturbances in the lower ionosphere.

Large-scale real-world radio signal recognition with deep learning

In the past ten years, many high-quality datasets have been released to support the rapid development of deep learning in the fields of computer vision, voice, and natural language processing. Nowadays, deep learning has become a key research component of the Sixth-Generation wireless systems(6G) with numerous regulatory and defense applications. In order to facilitate the application of deep learning in radio signal recognition, in this work, a large-scale real-world radio signal dataset is created based on a special aeronautical monitoring system-Automatic Dependent Surveillance-Broadcast(ADS-B). This paper makes two main contributions. First, an automatic data collection and labeling system is designed to capture over-the-air ADS-B signals in the open and real-world scenario without human participation. Through data cleaning and sorting, a high-quality dataset of ADS-B signals is created for radio signal recognition. Second, we conduct an in-depth study on the performance of deep learning models using the new dataset, as well as comparison with a recognition benchmark using machine learning and deep learning methods.Finally, we conclude this paper with a discussion of open problems in this area.

Detection and Classification on Amateur Drones Based on Cepstrum of Radio Frequency Signal

As a prospective component of the future air transportation system,unmanned aerial vehicles(UAVs)have attracted enormous interest in both academia and industry.However,small UAVs are barely supervised in the current situation.Crash accidents or illegal airspace invading caused by these small drones affect public security negatively.To solve this security problem,we use the back-propagation neural network(BPNN),the support-vector machine(SVM),and the k-nearest neighbors(KNN)method to detect and classify the non-cooperative drones at the edge of the flight restriction zone based on the cepstrum of the radio frequency(RF)signal of the drone’s downlink.The signal from five various amateur drones and ambient wireless devices are sampled in an electromagnetic clean environment.The detection and classification algorithm based on the cepstrum properties is conducted.Results of the outdoor experiments suggest the proposed workflow and methods are sufficient to detect non-cooperative drones with an average accuracy of around 90%.The mainstream downlink protocols of amateur drones can be classified effectively as well.

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.

A Virtual TDOA Localization Scheme of Chinese DTMB Signal in Radio Monitoring Networks

As the radio communications technology widely used,wireless location technology plays a more important role in maintaining the order of the air waves.However concretely effective symbol calibration method with regard to Chinese DTMB signal of different frame mode is quite under research due to the multiple structure of DTMB signal.In this paper,we propose a Time Difference of Arrival(TDOA)-based passive location scheme using least square principle.Utilizing the large number of anchor nodes in wireless monitoring network,a novel algorithm is formulated to solve the None-LineOf-Sight problem.The derived Cramer Rao Lower Bound of the localization method guides to the accuracy of the position outcome with regards to the calibration precision.In contrast with traditional multi-terminal location schemes,our location scheme can reduce calculation complexity and location costs abruptly.A twostep NLOS identification algorithm is proposed.Computer simulation is employed to verify the well performance of the calibration method of3-4 dB superiority than normal method and also the whole localization scheme for less than 50 meters through channel of SNR lower than dB.Simulation also shows that our algorithm can effectively identify NLOS path and improve positioning accuracy.

Breast Lump Recognition Algorithms Based on Ultrasound Radio-Frequency Signals

A method for evaluating the benign and malignant breast tumors based on radio?frequency(RF)data was explored by extracting the characteristic parameters of breast ultrasound RF signals.The breast biopsy data were used as the reference data for judging the lump benign or malignant.The extracted ultrasound RF data were reconstructed and segmented by computer aided method to obtain the breast tumor region of interest(ROI)and its characteristic parameters(entropy and standard deviation).The characteristic parameters were statistically analyzed to evaluate the relationship between characteristic parameters and benign or malignant breast tumors.The results indicate the entropy and standard deviation of normal region is much higher than that of lump region,which shows that the standard deviation and entropy characteristic parameters of ultrasonic RF signals are meaningful in the diagnosis of breast tumors.The proposed method provides a new direction for computer?aided diagnosis of benign and malignant breast tumors.

Photonic Vector Signal Generation by Frequency Sextupling for Radio Over Fiber Systems

To generate high-frequency radio frequency(RF) vector signals, a vector signal generation method by optical frequency sextupling using a dual-parallel modulator is proposed. The method modulates vector signal on +3 rd order optical sideband and local oscillator(LO) signal on-3 rd order sideband using the intermodulation process in the DPMZM. After suppressing of the optical carrier and other sidebands through proper adjustment for modulator biases and modulation index, a frequency sextupled millimeter-wave vector signal can be generated after photodetection. The frequency sextupling will lower the bandwidth of the modulator, the local oscillator and the driving circuits. In addition, the phase of generated signal is not distorted after detection, and the power fading after fiber transmission can be avoided. In the simulation, a 500-MSym/s QPSK signal at 60 GHz is generated by 10-GHz drive signal. After travelling over fiber with length of 20/30/40-km, receiver power penalty keeps below 2.5 dB.

Radio Frequency Environment Effect Algorithms and Implementation in Signal-level Radar System Simulation

In radar system simulation,the reliability of simulation results depends not only on radar and target models,but also on radio frequency (RF) environment models,including clutter,multipath,diffraction,atmosphere refraction and attenuation.In traditional radar function simulation,all of these factors are grouped into a single pattern-propagation factor and can only give limited information for radar models.In signal-level simulation,radar models require simulated echoes should include information such as delay,doppler frequency,polarization,etc.By discussing and analyzing the principles and algorithms of RF environment effects (clutter,multipath,diffraction,atmosphere refraction and attenuation),this paper is supposed to provide a general RF environment model in signal-level.Algorithms for the Weibull clutter with Gaussian power spectral density (PSD) is discussed;A standard multipath and diffraction algorithm is analyzed,and the spherical earth and knife edge(SEKE)diffraction algorithm is introduced;The ray-tracing algorithm and the effective earth model are discussed;Algorithms for the absorption of oxygen and vapor are introduced;For certain algorithms,some practical advice is given.Finally,an object-oriented RF environment effects model is implemented,which has been dedicatedly designed for signal-level simulations and can provide relatively authentic simulated RF environment for the signal-level simulation of radar systems.Two simulation examples including clutter model and multipath and diffraction model are carried out and analyzed.

基于GNU Radio和USRP2的未知信号检测

运用开源软件无线电(GNU's Not Unix Radio,GNU Radio)技术和与之配套的通用软件无线电外设(TheSecond-generation Universal Software Radio Peripheral,USRP2),设计出了未知无线电信号自动检测系统。系统采用能量检测法,能够快速识别一定频段内未知无线电信号,并记录其带宽、中心频率和起止时间,同时存储相应的同相正交(Inphaseand Quadrature,IQ)数据,为后续载频的精确估计提供必要的参数。在实际测试中发现,该系统检测速度快、准确率高,对未知强信号检测具有一定的可靠性和实用性。

基于GNU Radio的ADS-B信号收发系统设计

针对高集成度ADS-B系统不易开展创新性研究的问题,基于软件无线电设计了一套ADS-B信号收发系统;首先以可修改形式实现ADS-B报文编码、基带信号生成、前导脉冲检测、信号解调以及ADS-B信息解码等自定义GNU Radio模块的编写;然后创建ADS-B发射机和接收机流图,驱动硬件外设HackRF实现ADS-B信号的发射与接收;最后通过实验对各模块功能及数据接口进行测试;实验结果表明,该系统设计方案可行,ADS-B信号格式及报文广播速率符合Do-260B标准,且ADS-B接收机接收灵敏度为-68 dBm,信号检测率达89%。

基于GNU Radio架构的信号处理实验平台开发

开发了基于GNU Radio的信号分析与处理实验平台。借助GNU Radio完全开源的信号分析处理平台,既能够提供开放式可修改的模块库,以便快速建立关于信号处理的流程并进行内容设计、仿真,又能够用来连接真实的信号接收和处理系统,方便进行综合性和探究性实验设计。该实验平台的建立,方便学生以更加灵活的学习形式获取专业的资源,进行更加灵活多样的学习和互动,并有助于提高实验教学效果。

Signal Travel Time Anomaly between Earth and Solar Planets

Travel time anomaly in the communicatin of spatial instruments installed in solar planets and Earth are investigated in a model of gravity impact on radio signal propagation. Resulting travel times anomaly shows variations less than 10-3 seconds to and from Venus and Mars while Sun provides anomaly travel times of about -2 × 10-2 sec as backward signal needs more times than emitted signal from Earth. In the current explorations on Mars, the travel time anomaly may reach 1.8 × 10-4 sec as orbital Mars position pass through its minimum distance with respect to Earth. Implications of the difference between one and two-way travel times may be related to redshift/blueshift while travel time of received signal is less or greater than emitted signal.

The Refractive Effect of k-Factor on Radio Propagation over Lokoja, Nigeria

The effective earth radius factor(k-factor)has a refractive propagation effect on transmitted radio signals thus making its study necessary for the proper planning of terrestrial radio links and power budget.This study was carried out over the city of Lokoja,Nigeria,using ten years(2011 to 2020)atmospheric data of temperature,pressure and humidity both at the surface(12 m)and at 100 m AGL.The data were retrieved from European Centre for Medium-Range Weather Forecasts(ECMWF)ERA5.The k-factor yearly variation follows the same trend with minimum and maximum values obtained during dry and wet season months respectively.In addition,the highest mean value of 1.00042 was recorded in the month of August while the lowest value of 1.00040 was recorded in the month of January with an overall mean value of 1.0003.This value is less than the recommended standard of 1.33 by ITU-R.The propagation effect corresponding to k<1.33 is sub-refractive.The implication of this on radio wave propagation,especially terrestrial communications is that transmitted wireless signal is prone to losses.This can be mitigated through an effective power budget:Choice of transmitting antenna’s height and gain,so as to improve the Quality of Service over the study area.

基于GNU Radio和USRP新型软件频谱分析仪

提出了一种让模数转换器尽量靠近天线,由通用软件无线电外设实现简单信号处理,在GNU Radio开源软件平台上实现信号频谱分析的新型频谱分析仪的设计方法。与纯硬件实现的频谱分析仪相比,由于该新型频谱分析仪使用软件处理信号,其研发成本低,可以灵活配置。文中用C++和python语言开发频谱分析仪的软件模块,由于其扩展性和可移植性强,且开发周期短,大大降低了软件维护和升级成本。最后,通过测试验证了该软件频谱分析仪在实际环境中的可行性和有效性。

基于GNU Radio的雷达信号处理系统设计实现

针对现有雷达仿真系统的单线程运行模式在处理较大数据量或多任务执行时会造成CPU负担加重、导致系统运行速度缓慢与数据丢失,进而影响仿真测试的实效性等问题,提出了基于GNU Radio软件平台利用其多线程技术与模块化思想,同时设计并使用传输内存地址的方法来搭建雷达信号系统,提升计算机的资源利用率。多线程模式下的系统运行不仅能够对大量数据进行处理,而且能提升其处理数据的速度,同时兼具美观性与操作性。最后的测试数据表明了雷达信号处理系统的有效性,达到了预期的设计目标,满足了实际应用需求。