Adaptive detection of range-spread targets in homogeneous and partially homogeneous clutter plus subspace interference

Adaptive detection of range-spread targets is considered in the presence of subspace interference plus Gaussian clutter with unknown covariance matrix.The target signal and interference are supposed to lie in two linearly independent subspaces with deterministic but unknown coordinates.Relying on the two-step criteria,two adaptive detectors based on Gradient tests are proposed,in homogeneous and partially homogeneous clutter plus subspace interference,respectively.Both of the proposed detectors exhibit theoretically constant false alarm rate property against unknown clutter covariance matrix as well as the power level.Numerical results show that,the proposed detectors have better performance than their existing counterparts,especially for mismatches in the signal steering vectors.

Iterative Signal Detection Based Soft Interference Cancellation for Satellite-Terrestrial Downlink NOMA Systems

To improve the bit error rate(BER)performance of multi-user signal detection in satelliteterrestrial downlink non-orthogonal multiple access(NOMA)systems,an iterative signal detection algorithm based on soft interference cancellation with optimal power allocation is proposed.Given that power allocation has a significant impact on BER performance,the optimal power allocation is obtained by minimizing the average BER of NOMA users.According to the allocated powers,successive interference cancellation(SIC)between NOMA users is performed in descending power order.For each user,an iterative soft interference cancellation is performed,and soft symbol probabilities are calculated for soft decision.To improve detection accuracy and without increasing the complexity,the aforementioned algorithm is optimized by adding minimum mean square error(MMSE)signal estimation before detection,and in each iteration soft symbol probabilities are utilized for soft-decision of the current user and also for the update of soft interference of the previous user.Simulation results illustrate that the optimized algorithm i.e.MMSE-IDBSIC significantly outperforms joint multi-user detection and SIC detection by 7.57dB and 8.03dB in terms of BER performance.

Turbo Message Passing Based Burst Interference Cancellation for Data Detection in Massive MIMO-OFDM Systems

This paper investigates the fundamental data detection problem with burst interference in massive multiple-input multiple-output orthogonal frequency division multiplexing(MIMO-OFDM) systems. In particular, burst interference may occur only on data symbols but not on pilot symbols, which means that interference information cannot be premeasured. To cancel the burst interference, we first revisit the uplink multi-user system and develop a matrixform system model, where the covariance pattern and the low-rank property of the interference matrix is discussed. Then, we propose a turbo message passing based burst interference cancellation(TMP-BIC) algorithm to solve the data detection problem, where the constellation information of target data is fully exploited to refine its estimate. Furthermore, in the TMP-BIC algorithm, we design one module to cope with the interference matrix by exploiting its lowrank property. Numerical results demonstrate that the proposed algorithm can effectively mitigate the adverse effects of burst interference and approach the interference-free bound.

A Proposed Solution to the Interference of IgG Kappa-Type M Protein on LDL-C Detection

Objective:To explore the interference of monoclonal immunoglobulin(M protein)on the detection of serum LDL-C in patients with multiple myeloma,improve the understanding of this matter,determine and establish the correct method,and provide more accurate clinical results through this case.Methods:A case was selected for analysis by the direct method.Results:The interference of IgG kappa-type M protein on LDL-C detection could not be completely eliminated by the enzymatic method.Conclusion:IgG-type type M protein affects the detection of LDL-C by the enzymatic method;thus,light reagents can be used with the direct method for detection.

Multifunctional MXene/Carbon Nanotube Janus Film for Electromagnetic Shielding and Infrared Shielding/Detection in Harsh Environments

Multifunctional,flexible,and robust thin films capable of operating in demanding harsh temperature environments are crucial for various cutting-edge applications.This study presents a multifunctional Janus film integrating highly-crystalline Ti_(3)C_(2)T_(x) MXene and mechanically-robust carbon nanotube(CNT)film through strong hydrogen bonding.The hybrid film not only exhibits high electrical conductivity(4250 S cm^(-1)),but also demonstrates robust mechanical strength and durability in both extremely low and high temperature environments,showing exceptional resistance to thermal shock.This hybrid Janus film of 15μm thickness reveals remarkable multifunctionality,including efficient electromagnetic shielding effectiveness of 72 dB in X band frequency range,excellent infrared(IR)shielding capability with an average emissivity of 0.09(a minimal value of 0.02),superior thermal camouflage performance over a wide temperature range(−1 to 300℃)achieving a notable reduction in the radiated temperature by 243℃ against a background temperature of 300℃,and outstanding IR detection capability characterized by a 44%increase in resistance when exposed to 250 W IR radiation.This multifunctional MXene/CNT Janus film offers a feasible solution for electromagnetic shielding and IR shielding/detection under challenging conditions.

Experimental analysis on bolt interference during advanced water detection with the mine transient electromagnetic method

During advanced water detection using the transient electromagnetic method, the exploration effect for water-rich area is often poor due to the interference of bolts that are distributed in different positions in working face. Thus, the study on the interference characteristics of bolts in different states has important directive significance for improving the acquisition quality and data processing method in water detection. Based on the analysis of the distribution laws of magnetic field excited by small multi-turn coincident loop in full space of homogeneity, the test on the interference of bolts has been designed in the mine. Through drilling 18 holes around the overlapping coil in the working face, mass data are collected in order with the posi- tion change and the exposed bolt length. The results of comprehensive data analysis show that the transient electromagnetic field is strongly interfered as the distance between the bolt and the center of the coil is less than 3 m, and the interference varies greatly as the distance varies. On the other hand, the field induced by the bolts can be ignored as the distance exceeds 3 m. The findings can help to improve data acquisition and correction during advanced water detection when using the transient electromagnetic method.

A simplified method for local tool interference detection and tool position modification during five-axis ball-end milling process

Five-axis ball-end milling is commonly used to machine the complex surfaces. Local tool interference phenomenon which often occurs in five-axis milling should be urgently solved. In this paper, a simplified method to detect the occurrence of local tool interference and modify tool position is proposed. First, the detection matrix is established to detect local tool interference at all the cutter location points on tool path simultaneously in five-axis ball-end milling of complex surfaces. The algorithm of detection matrix based on point arithmetic is simple. Secondly, the new coordinates of the modified interfering-free points are obtained precisely by using the genetic algorithm. The feasibility of the method is validated by simulation in Matlab. This research is benefit to simplify the calculation of local tool interference detection and tool position modification.

Research on Influence of Electromagnetic Interference on X-Ray Digital Detection

X-ray digital imaging technology has found wide application owing to its advantages of real-time, visualization and rapid imaging. In substations the substantial electromagnetic interference has some influence on the live detection by the X-ray digital imaging technology, hindering the promotion of the technology in the detection of electric equipment. Based on a large number of field tests, the author carded out a series of researches on electromagnetic interference protection measures, image de-noising, and image enhancement algorithms.

A Linear Interference Cancellation Multi-User Detector for Synchronous CDMA Communications

This paper describes a linear interference cancellation multi user detector for synchronous DS CDMA systems under the condition that all spread spectrum code waveforms have the constant cross correlating coefficients. The basic idea is to get the estimation for total multiple access interference (MAI) of all users using a reference code waveform, then subtract the total MAI from the received signal. The structure of such a detector is nearly similar to the conventional detector. The BER expression obtained in the paper shows significant performance improvement compared to the other detectors.

ADS-B Anomaly Data Detection Model Based on Deep Learning and Difference of Gaussian Approach

Due to the influence of terrain structure,meteorological conditions and various factors,there are anomalous data in automatic dependent surveillance-broadcast(ADS-B)message.The ADS-B equipment can be used for positioning of general aviation aircraft.Aim to acquire the accurate position information of aircraft and detect anomaly data,the ADS-B anomaly data detection model based on deep learning and difference of Gaussian(DoG)approach is proposed.First,according to the characteristic of ADS-B data,the ADS-B position data are transformed into the coordinate system.And the origin of the coordinate system is set up as the take-off point.Then,based on the kinematic principle,the ADS-B anomaly data can be removed.Moreover,the details of the ADS-B position data can be got by the DoG approach.Finally,the long short-term memory(LSTM)neural network is used to optimize the recurrent neural network(RNN)with severe gradient reduction for processing ADS-B data.The position data of ADS-B are reconstructed by the sequence to sequence(seq2seq)model which is composed of LSTM neural network,and the reconstruction error is used to detect the anomalous data.Based on the real flight data of general aviation aircraft,the simulation results show that the anomaly data can be detected effectively by the proposed method of reconstructing ADS-B data with the seq2seq model,and its running time is reduced.Compared with the RNN,the accuracy of anomaly detection is increased by 2.7%.The performance of the proposed model is better than that of the traditional anomaly detection models.

RFI Detection for Multichannel HRWS SAR System Based on Spatial Cross Correlation

Multichannel high-resolution and wide-swath(HRWS)imaging is an advanced digital beamforming technique for future synthetic aperture radar(SAR)systems.However,radio frequency interference(RFI)is a critical concern for HRWS SAR missions,which distorts measure-ments and produces image artifacts.In this paper,the spatial cross-correlation coefficients of multichannel HRWS SAR signals are investigated for RFI detection.It is found when the two channels are correlated,RFI-polluted areas present lower coherence values than non-polluted areas in the same scenarios,which makes previous methods fail.Further,this paper studies the case of two fully decorrelated channels to maximize the coherence difference among RFI and target echoes,and RFI detection is realized by exploiting the anomaly value of coherence.Experimental results of real air-borne multichannel SAR data demonstrate that the RFI can be detected successfully.

Leak Detection of Gas Pipelines Based on Characteristics of Acoustic Leakage and Interfering Signals

When acoustic method is used in leak detection for natural gas pipelines,the external interferences including operation of compressor and valve,pipeline knocking,etc.,should be distinguished with acoustic leakage signals to improve the accuracy and reduce false alarms.In this paper,the technologies of extracting characteristics of acoustic signals were summarized.The acoustic leakage signals and interfering signals were measured by experiments and the characteristics of time-domain,frequency-domain and time-frequency domain were extracted.The main characteristics of time-domain are mean value,root mean square value,kurtosis,skewness and correlation function,etc.The features in frequency domain were obtained by frequency spectrum analysis and power spectrum density,while time-frequency analysis was accomplished by short time Fourier transform.The results show that the external interferences can be removed effectively by the characteristics of time domain,frequency domain and time-frequency domain.It can be drawn that the acoustic leak detection method can be applied to natural gas pipelines and the characteristics can help reduce false alarms and missing alarms.

基于到达时间间隔差的ADS-B位置消息验证方法

广播式自动相关监视(ADS-B)是一种新型的航空器监视技术,具有定位精度高、更新速度快及覆盖范围广等优势,在民用航空监视领域获得广泛应用。由于ADS-B消息以广播方式传输,未采用加密与认证机制,ADS-B系统易受外部欺骗源的干扰。为解决该问题,提出了一种基于到达时间间隔差(IDOA)的ADS-B位置消息验证方法。建立基于IDOA的ADS-B位置消息验证系统模型,理论分析给出检验统计量的表达式及其统计特性,进一步分析给出检测门限的确定方法,通过仿真验证所提方法的正确性与有效性。结果表明:所提方法与基于到达时间差(TDOA)的验证方法具有相同的检测性能,且对时间测量误差和ADS-B位置误差不敏感,但所提方法可克服基于TDOA的验证方法存在的对地面站时间同步误差敏感的缺点。

ADS-B系统干扰检测技术研究

自动相关监视广播(Automatic Dependent Surveillance-Broadcast,ADS-B)是一种航空电子设备,通过无线方式将飞机的位置、速度和其他相关信息广播给地面控制器和其他飞行中的飞机。然而,ADS-B系统容易受到恶意干扰和误报干扰的影响,这可能对航空安全和飞行管制造成严重威胁。为了保证ADS-B系统的可靠性和安全性,研究人员提出了各种干扰检测技术。本文对现有ADS-B干扰检测技术进行了综述,并对未来的研究方向提出了展望。

Target detection using CDMA based passive bistatic radar

Recently, the code division multiple access （CDMA） waveform exists in the large area across the world. However, when using the CDMA system as the illuminator of opportunity for the passive bistatic radar （PBR）, there exists interference not only from the base station used as the illuminator of opportunity but also from other base stations with the same frequency. And be cause in the CDMA system, the signal transmitted by each base station is different, using the direct signal of one base station can not cancel the interference from other base stations. A CDMA based PBR using an element linear array antenna as both the reference antenna and surveillance antenna is introduced. To deal with the interference in this PBR system, an adaptive temporal cancellation algorithm is used to remove the interference from the base station used as the illuminator of opportunity firstly. And then a robust adaptive beamformer is used to suppress the interference from other base stations. Finally, the preliminary experiment re sults demonstrate the feasibility of using CDMA signals as a radar waveform.

An improved linear dispersion codes transmission scheme based on OSIC detection

Linear dispersion codes (LDCs) were originally designed based on maximum likelihood detection. They do not have good performance when using ordered successive interference cancellation (OSIC) detection. In this paper,we propose a new improved linear dispersion codes transmission scheme to combat performance loss of original LDCs when using OSIC detection. We introduce an interleaver to each data substream transmitted over different antennas after LDCs encoder. Furthermore,a new computer search criterion for a linear transformation matrix is also proposed. New search criterion is to minimize the symbol error rate based on OSIC detection. Computer simulations show that the performance of proposed LDCs transmission scheme is better than the original LDCs.

Combined Transmission Interference Spectrum of No Core Fiber and BP Neural Network for Concentration Sensing Research

To investigate wavelength response of the no core fiber（NCF）interference spectrum to concentration,a three-layer back propagation（BP）neural network model was established to optimize the concentration sensing data.In this method,the measured wavelength and the corresponding concentration were trained by a BP neural network,so that the accuracy of the measurement system was optimized.The wavelength was used as the training set and got into the input layer of the three layer BP network model which is used as the input value of the network,and the corresponding actual concentration value was used as the output value of the network,and the optimal network structure was trained.This paper discovers a preferable correlation between the predicted value and the actual value,where the former is approximately equal to the latter.The correlation coefficients of the measured and predicted values for a sucrose concentration were 1.000 89 and 1.003 94;similarly,correlations of0.999 51 and 1.018 8 for a glucose concentration were observed.The results demonstrate that the BP neural network can improve the prediction accuracy of the nonlinear relationship between the interference spectral data and the concentration in NCF sensing systems.

Joint Optimal Sensing Threshold and Subcarrier Power Allocation in Wideband Cognitive Radio for Minimising Interference to Primary User

Cognitive Radio （CR） can use the fre- quency band allocated to a Primary User （PU） on the premise that it will prevent significant of avoiding causing great interference to the PU. In this paper, we consider a wideband CR system where the Secondary User （SU） mini- raises its interference to the PU by jointly al- locating the optimal sensing threshold and sub- carrier power. A multi-parameter optimization problem is formulated to obtain the joint opt- imal allocation by alternating direction opti- mization, which minimises the total interfer- ence to the PU over all of the subcarriers sub- ject to the constraints on the throughput, Bit Error Rate （BER） and maximal total power of the SU, the subcarrier rate and interference power of the PU, and the false alarm and mis- detection probabilities of each subcarrier. The simulation results show that the proposed joint allocation algorithm can achieve the desired mitigation on the interference to the PU at the different subcarrier gains.

Characteristics of the propagation of partial discharge ultrasonic signals on a transformer wall based on Sagnac interference

The acoustic emission(AE)method has been widely recognized for the detection of incipient insulation fault phenomenon(partial discharge,PD)in power transfomiers,nevertheless,the installation and placement of AE sensors should be taken into full consideration.In this manuscript,a three-dimensional multiphysics model was established and simulated to research the characteristics of the propagation in the transformer wall.Furthermore,a piezoelectric transducer was used to detect PD ultrasonic signals and verify the simulation results in the laboratory.To ensure the accuracy of the detection,an optical fiber sensor based on the Sagnac interference principle was designed and adopted.The variation of the amplitude of the ultrasonic signal with distance reveals the characteristics of the ultrasonic signal propagating in the transformer wall.The distribution of sound pressure on the upper and lower surfaces of the simulation model proved that ultrasonic waves propagate in the form of symmetrical Lamb waves in the transformer wall.Moreover,the amplitude of the AE attenuates due to absorption and refraction loss,and local fluctuations on account of acoustic interference.Thus,a stable signal detected by an AE sensor does not represent the absence of PD in a transfomier.To improve the reliability of AE detection,it is proposed in this manuscript that repeated movement of the AE sensor is necessary to obtain a suitable measurement position.Similarly,it is necessary to adjust the position of the AE sensor in order to locate the PD source well.In addition,this study is expected to provide a theoretical analysis and a fiber sensor to address the problem of sensor placement in AE detection.

NOVEL ADAPTIVE MULTIUSER DETECTIONALGORITHM BASED ON WAVELET TRANSFORM

The wavelet transform-based adaptive multiuser detection algorithm is presented. The novel adaptive multiuser detection algorithm uses the wavelet transform for the preprocessing, and wavelet-transformed signal uses LMS algorithm to implement the adaptive multiuser detection. The algorithm makes use of wavelet transform to divide the wavelet space, which shows that the wavelet transform has a better decorrelation ability and leads to better convergence. White noise can be wiped off under the wavelet transform according to different characteristics of signal and white noise under the wavelet transform. Theoretical analyses and simulations demonstrate that the algorithm converges faster than the conventional adaptive multiuser detection algorithm, and has the better performance. Simulation results reveal that the algorithm convergence relates to the wavelet base, and show that the algorithm convergence gets better with the increasing of regularity for the same series of the wavelet base. Finally the algorithm shows that it can be easily implemented.