Interference Detection Algorithm Research Articles

Joint Interference Detection Method for DSSS Communications Based on the OMP Algorithm and CA-CFAR

The existing direct sequence spread spectrum (DSSS) communications interference detection algorithms are confined to the high sampling rate. In order to solve this problem, algorithm for DSSS communications interference detection was designed based on compressive sensing (CS). First of all, the orthogonal matching pursuit (OMP) algorithm was applied to the interference detection in DSSS communications, the advantages and weaknesses of the algorithm were analyzed; Secondly, according to the weaknesses of the OMP algorithm, a joint interference detection method based on the OMP algorithm and cell average constant false alarm rate (CA-CFAR) was proposed. The theoretical analyze and computer simulation all proved the effectiveness of the new algorithm. The simulation results show that the new method not only could achieve the interference detection, but also could estimate the interference quantity effectively.

Low-level radio-frequency interference detection algorithm based on European Centre for Medium-Range Weather Forecasting for Soil Moisture and Ocean Salinity

At present, the Soil Moisture and Ocean Salinity (SMOS) mission is severely affected by radio frequency interferences (RFIs), and the detection of low-level RFI-contamination brightness temperatures (BTs) is still a challenge in SMOS. A low-level RFI detection algorithm is proposed, which is based on the soil surface temperature products provided by the European Centre for Medium-Range Weather Forecasting. The algorithm is analyzed in terms of RFI-flagged snapshot, RFI-flagged probability, and localization accuracy. The performance of the algorithm is demonstrated by SMOS data. The results show this algorithm can detect and flag more low-level RFI-contamination BTs and show a better performance.

Ranking Fragment Ions Based on Outlier Detection for Improved Label-Free Quantification in Data-Independent Acquisition LC-MS/MS.

Data-independent acquisition LC-MS/MS techniques complement supervised methods for peptide quantification. However, due to the wide precursor isolation windows, these techniques are prone to interference at the fragment ion level, which, in turn, is detrimental for accurate quantification. The nonoutlier fragment ion (NOFI) ranking algorithm has been developed to assign low priority to fragment ions affected by interference. By using the optimal subset of high-priority fragment ions, these interfered fragment ions are effectively excluded from quantification. NOFI represents each fragment ion as a vector of four dimensions related to chromatographic and MS fragmentation attributes and applies multivariate outlier detection techniques. Benchmarking conducted on a well-defined quantitative data set (i.e., the SWATH Gold Standard) indicates that NOFI on average is able to accurately quantify 11-25% more peptides than the commonly used Top-N library intensity ranking method. The sum of the area of the Top3-5 NOFIs produces similar coefficients of variation as compared to that with the library intensity method but with more accurate quantification results. On a biologically relevant human dendritic cell digest data set, NOFI properly assigns low-priority ranks to 85% of annotated interferences, resulting in sensitivity values between 0.92 and 0.80, against 0.76 for the Spectronaut interference detection algorithm.

Block‐flow noise power estimation algorithm for pulsed interference detection of GNSS receivers

The noise power estimation for pulsed interference detection in global navigation satellite system (GNSS) receivers is considered. Previous effective consecutive mean excision (CME) related algorithms in this area work in an inter-block iterative fashion and the convergent process is usually quite time-consuming and needs a large storage space. A block-flow manner based on the backward CME (BCME) algorithm to overcome these problems is proposed. Numerical results show that the method decreases the computation and storage requirements of BCME, and possesses closer convergence properties.

적응 페이딩 칼만 필터를 이용한 기준국 기반의 램프 형태 GNSS 기만신호 검출 알고리즘

In this paper, a GNSS interference detection algorithm based on an adaptive fading Kalman filter is proposed to detect a spoofing signal which is one of the threatening GNSS intentional interferences. To detect and mitigate the spoofing signal, the fading factor of the filter is used as a detection parameter. For simulation, the effect of the spoofing signal is modeled by the ramp type bias error of the pseudorange to emulate a smart spoofer and the change of the fading factor value according to ramp type bias error is quantitatively analyzed. In addition, the detection threshold is established to detect the spoofing signal by analyzing the change of the error covariance and the effect of spoofing is mitigated by controlling the Kalman gain of the filter. To verify the performance analysis of the proposed algorithm, various simulations are implemented. Through the results of simulations, we confirmed that the proposed algorithm works well.

하향링크 다중 사용자 MIMO 통신 시스템을 위한 확장형 고정복잡도 스피어 복호기

본 논문에서는, 하향 다중 사용자 MIMO 환경에서 간섭 검출 및 제거를 하기위해 확장된 fixed-complexity sphere decoder (FSD) 알고리즘이 제안되었다. 제안된 알고리즘은, generalized sphere decoder (GSD) 알고리즘을 이용한 채널행렬 확장과 간섭신호와 요구신호를 고려한 채널행렬 순서화를 통해 FSD 알고리즘을 간섭신호 검출에 활용 가능하도록 확장 하였다. IEEE802.11ac의 통신모드 중 네 명의 다중 사용자에게 각각 702 Mbit/s 전송이 가능한 환경의 몬테카를로실험을 통해서, 제안된 알고리즘이 10% packet error rate기준으로 간섭제거 기능이 없는 maximum-likelihood 검출성능 대비 <TEX>$E_b/N_0$</TEX>가 약 3 dB 향상됨을 보여주었다. In this paper, a extension of a fixed-complexity sphere decoder (FSD) to perform interference signal detection and cancelling is proposed for downlink multiuser multiple input-multiple output (MIMO) communication system. It is based on the application of channel matrix expansion on generalized sphere decoder (GSD), and modification of the channel matrix ordering scheme to a FSD algorithm for interference detection. A Monte Carlo simulation shows that the proposed algorithm improves the receiver performance by 3 dB as compared to maximum likelihood detection without interference cancelling at 10% packet error rate in configuration of 702 Mbit/s datarate for four users respectively on IEEE802.11ac.

Fundamental reconfiguration theory of chain-type modular reconfigurable mechanisms

This article focuses on the study of geometry constraints, motion sequence, isomorphism and interference issues of the chain-type modular reconfigurable mechanisms. The geometry representation of module is accomplished by employing the Clifford algebra. A new expression of discrete movement—“motion sequence” which is combined with exponential formula for kinematics is proposed to calculate the position and orientation of each module. Meanwhile, isomorphism is identified by using the adjacency matrix. Furthermore, an interference detection algorithm on the basis of Clifford algebra is investigated for interference detection during the movement. Finally, the principle of reconfiguration of modular mechanisms is presented in detail. Case studies are demonstrated to verify the validity and the effectiveness of our fundamental reconfiguration theory to analyze modular reconfigurable systems.

Intentional GNSS Interference Detection and Characterization Algorithm Using AGC and Adaptive IIR Notch Filter

A Ground Based Augmentation System (GBAS) is an enabling technology for an aircraft’s precision approach based on a Global Navigation Satellite System (GNSS). However, GBAS is vulnerable to interference, so effective GNSS interference detection and mitigation methods need to be employed. In this paper, an intentional GNSS interference detection and characterization algorithm is proposed. The algorithm uses Automatic Gain Control (AGC) gain and adaptive notch filter parameters to classify types of incoming interference and to characterize them. The AGC gain and adaptive lattice IIR notch filter parameter values in GNSS receivers are examined according to interference types and power levels. Based on those data, the interference detection and characterization algorithm is developed and Monte Carlo simulations are carried out for performance analysis of the proposed method. Here, the proposed algorithm is used to detect and characterize single-tone continuous wave interference, swept continuous wave interference, and band-limited white Gaussian noise. The algorithm can be used for GNSS interference monitoring in an excessive Radio Frequency Interference environment which causes loss of receiver tracking. This interference detection and characterization algorithm will be used to enhance the interference mitigation algorithm.

A GNSS Interference Detection Method Based on Multiple Ground Stations

For a GNSS receiver's robustness against RFI and the high accuracy of navigation solution in GNSS, interference source detection and mitigation are needed. In this paper, an adaptive lattice IIR notch filter is employed to track single-tone continuous wave and swept continuous wave interference signals, and an interference detection method is proposed. Furthermore, this paper presents interference source characterization algorithm using multiple ground stations' interference detection results. The measurement of the signal powers from each ground station is used to build weighting factors to estimate the type of the interference. The performance of interference detection algorithm is simulated for scenarios of GPS signal in the presence of single-tone continuous wave interference and swept continuous wave interference.

Analysis of Radio Frequency Interference Detection Algorithms in the Angular Domain for SMOS

Radio frequency interference (RFI) detection techniques have different challenges and opportunities for interferometric radiometers such as the Microwave Imaging Radiometer using Aperture Synthesis on the Soil Moisture and Ocean Salinity (SMOS) mission. SMOS does not have highly oversampled temporal resolution or subband filters for oversampled spectral resolution, as do other radiometers with enhanced RFI detection capabilities. It does, however, have multisampled angular resolution in the sense that a single location is viewed from many different angles of incidence. This paper compares and contrasts RFI detection algorithms that use measurements made at a variety of different levels of SMOS signal processing, including the visibility domain, brightness temperature spatial domain, and brightness temperature angular domain. The angular domain detection algorithm, in particular, is developed and characterized in detail. Examples of the algorithms applied to cases with RFI (to assess detection skill) and without RFI (to assess false-alarm behavior) are considered.

Radio Frequency Interference Detection and Mitigation Algorithms Based on Spectrogram Analysis

Radio Frequency Interference (RFI) detection and mitigation algorithms based on a signal’s spectrogram (frequency and time domain representation) are presented. The radiometric signal’s spectrogram is treated as an image, and therefore image processing techniques are applied to detect and mitigate RFI by two-dimensional filtering. A series of Monte-Carlo simulations have been performed to evaluate the performance of a simple thresholding algorithm and a modified two-dimensional Wiener filter.

Radio-Frequency Interference Detection and Mitigation Algorithms for Synthetic Aperture Radiometers

The European Space Agency (ESA) successfully launched the Soil Moisture and Ocean Salinity (SMOS) mission in November 2, 2009. SMOS uses a new type of instrument, a synthetic aperture radiometer named MIRAS that provides full-polarimetric multi-angular L-band brightness temperatures, from which regular and global maps of Sea Surface Salinity (SSS) and Soil Moisture (SM) are generated. Although SMOS operates in a restricted band (1400–1427 MHz), radio-frequency interference (RFI) appears in SMOS imagery in many areas of the world, and it is an important issue to be addressed for quality SSS and SM retrievals. The impact on SMOS imagery of a sinusoidal RFI source is reviewed, and the problem is illustrated with actual RFI encountered by SMOS. Two RFI detection and mitigation algorithms are developed (dual-polarization and full-polarimetric modes), the performance of the second one has been quantitatively evaluated in terms of probability of detection and false alarm (using a synthetic test scene), and results presented using real dual-polarization and full-polarimetric SMOS imagery. Finally, a statistical analysis of more than 13,000 L1b snap-shots is presented and discussed.

An Autonomous Interference Detection and Filtering Approach Applied to Wind Profilers

An autonomous interference detection and filtering algorithm has been developed for removing the interference bands generated in the Doppler spectra of mesosphere-stratosphere-troposphere (MST) radar signals. The technique, implemented with the MST radar at Gadanki (13.5° N, 79° E), is based on identifying interferencelike band signals using a statistical signal variance approach for fixing the amplitude threshold, through which detecting the interference frequency and designing an adaptable notch filter to filter the undesired frequency bands are done. Signals received from the MST radar are sometimes contaminated with interference signals received from other objects or generated within the system through arcing of high-power devices. Multiple interference bands with different characteristics are observed in the power spectra, which contaminate the wind information and other atmospheric signals. The autonomous interference detection and filtering algorithm is applied to various cases, and it is found that the interference signals could effectively be removed, leaving behind the original signals. By this approach, the effective number of signal samples obtained is increased, which helps one to improve the temporal resolution.

Energy-efficient detection of intermittent interference in wireless sensor networks

Communications of low-power sensor nodes are easily corrupted by transmissions of collocated devices that inducing packet losses might increase data delay and energy consumption. Dynamic Spectrum Access mechanisms can mitigate these problems. These approaches allow frequency agile sensor nodes to avoid frequency bands experiencing high interference and select channels suitable for their transmissions. In this context, detecting interference and identifying spectrum opportunities in a reliable and efficient manner becomes a task of vital importance. In this paper we propose a new interference detection algorithm accounting both for energy and complexity constraints of sensor motes as well as for the intermittent nature of interference typically experienced by sensor networks in unlicensed bands. We develop an analytical framework that allows to explicitly characterise the performance of our algorithm and also implement it on the TMote Sky sensor platform. Experimental results clearly demonstrate the capabilities of the proposed scheme to identify interfered channels.

Slice overlap-detection algorithm for process planning in multiple-material stereolithography

Recently, a multiple-material stereolithography (MMSL) system was introduced, which included the novel feature of stacking different photocurable resins to produce a multiple-material part. This process is capable of fabricating intricately detailed parts with smooth surface finish and internal structures of various colors. However, the MMSL system requires a washing process when switching materials, and this additional step increases the fabrication time and also introduces deformations in the build structure as registration errors accumulate. Consequently, reducing the number of material changeovers in this process is a priority, and the minimum number of changeovers is imposed in part by the sweep interference between layers of different materials. Fortunately, the use of low-viscosity resins permits possible fabrication without sweeping. As a result, multiple layers of one material can be continuously built without changing resins, and subsequently, a different low-viscosity material can be added without resulting in sweep obstruction with the original layers. In this paper, a stacking simulation, which determines the maximum number of layers possible to be continuously built between material changeovers, is described. This paper presents a novel interference-detection algorithm, which identifies interference by inspecting the overlap between loop segments. In addition, the algorithm successfully manages the triangulation errors that occur at a curved surface when two materials are adjacent within a layer. Finally, several practical examples are shown to verify the algorithm and provide compelling evidence that the proposed algorithm is effective and applicable in MMSL.

Use of Neural Networks for Identification of Artifacts in Electroencephalographic Signals Decomposed Using Wavelet Packet Transform

An algorithm for automatic interference (artifact) detection is suggested. This algorithm detects interference (artifact) as a component of EEG signals. The algorithm is based on approximation of electrophysiological signal using neural network model decomposition using the wavelet packet transform.

Detection of Radio-Frequency Interference for the Aquarius Radiometer

A radio-frequency interference (RFI) detection algorithm has been developed for the Aquarius microwave radiometer. The algorithm compares individual brightness temperature samples with a local mean obtained from neighboring samples. If the sample under test significantly deviates from the local mean, then it is assumed to be corrupted by RFI. The algorithm has several adjustable parameters to optimize RFI detection. The performance of the algorithm has been characterized as a function of these parameters using a new form of RFI ldquoground truthrdquo that is based on the kurtosis of the amplitude distribution of the predetected voltages of a radiometer. Ground-based radiometric data obtained from the JPL-PALS campaign were used to assess the performance of the algorithm. False-alarm rates and the dependence of false alarms on worst case naturally occurring brightness temperature variations on orbit are determined as functions of the adjustable parameters of the algorithm.

Power-Line Interference Detection and Suppression in ECG Signal Processing

A novel power-line interference (PLI) detection and suppression algorithm is presented to preprocess the electrocardiogram (ECG) signals. A distinct feature of this proposed algorithm is its ability to detect the presence of PLI in the ECG signal before applying the PLI suppression algorithm. No PLI suppression operation will be performed if PLI is not detected. We propose a PLI detector that employs an optimal linear discriminant analysis (LDA) algorithm to make a decision for the PLI presence. An efficient recursive least-squares (RLS) adaptive notch filter is also developed to serve the purpose of PLI suppression. Experimental results demonstrate superior performance of this proposed algorithm.

Interference detection for direct tool path generation from measured data points

One of the main issues of the reverse engineering (RE) is the duplication of an existing physical part whose geometric information is partially or completely unavailable in measured form. In some industrial applications, physical parts are duplicated using three-axis CNC machines and ball-end mills. Many researches studied the problem of direct tool path generation from measured data point. However, up to the present, it appears that there is no reported study on interference detection in paths generated directly from measured data points. Interference detection is a curial problem in direct tool path generation from measured data points. This paper discusses the problem of local and global interference detection for three-axis machining in RE and proposes algorithms for local and global interference detection. With these algorithms, the measured data points captured from a physical part are analyzed and classified according to the shapes of the part. The method has been tested with several industrial parts, and it is shown to be robust and efficient especially for the part with free-form surfaces.

Collision Free Path Planning of Cooperative Crane Manipulators Using Genetic Algorithm

This paper presents a new approach for automated path planning of cooperative crane manipulators using a genetic algorithm (GA). The inverse kinematic problem, i.e., determining the joint angle configuration for the cooperative crane manipulator system in moving the object from pick location to place location, is defined as an optimization problem and solved using GA. For generating the collision-free path, GA with an interference detection algorithm is employed and search is made in the manipulator joint angle space (configuration space). The effectiveness of the proposed approach for automated path planning is demonstrated by comparing the performance of the present approach with the earlier heuristic search proposed by Sivakumar et al. The GA approach finds a near-optimal path with lower path cost and less computational time than earlier heuristic searches.