IET Signal Processing最新文献

{"title":"An Improved Lightweight YOLO Algorithm for Recognition of GPS Interference Signals in Civil Aviation","authors":"Mian Zhong,&nbsp;Maonan Hu,&nbsp;Fei Hu,&nbsp;Lei Xu,&nbsp;Jiaqing Shen,&nbsp;Yutao Tang,&nbsp;Hede Lu,&nbsp;Chao Zhou","doi":"10.1049/2024/9927636","DOIUrl":"https://doi.org/10.1049/2024/9927636","url":null,"abstract":"<div>\u0000 <p>Considering several sources that cause global position system (GPS) interference in civil aviation and the challenges faced by interference recognition algorithms in terms of efficiency and accuracy, we propose an improved You Only Look Once (YOLO)v7-CHS algorithm (YOLOv7-CHS) and investigate its effectiveness in identifying GPS signals and different types of interference signals. First, continuous wavelet transform (CWT) is introduced as a method for processing and analyzing signals in the time–frequency (TF) domain to effectively obtain their temporal and spectral characteristic information. Second, the ConvNeXt structure is integrated into the YOLOv7 backbone network to create a ConvNeXtBlock (CNeB) module to enhance the classification and recognition accuracy of interference signals. Additionally, an attention mechanism is introduced to further improve model recognition accuracy. To effectively improve the capability of signal feature extraction and mitigate the impact of background noise on TF feature suppression, we have integrated the efficient channel attention (ECA) channel attention module with the convolutional block attention module (CBAM) spatial attention module, thereby proposing a hybrid CBAM and ECA (HCE) attention module. Last, to address issues arising from accidental deletion of detection frames and multipath interference negatively affecting model recognition performance, we have employed the soft nonmaximum suppression (Soft-NMS) algorithm while selecting an optimal loss function through comparative analysis. The comparative evaluation experimental results under different circumstances show that YOLOv7-CHS achieves recognition accuracies of 98.0% and 99.6% for various types of signals, respectively. These values represent an increase of 1.7% and 1%, respectively, compared to YOLOv7. Moreover, in terms of lightweight indicators, YOLOv7-CHS exhibits a significant improvement in performance: the frames per second (FPS) is increased by 75.1, the number of parameters (Params) was reduced by 4.75 M, and giga floating point operations per second (GFLOPs) were reduced by 65.9 G while effectively enhancing recognition capabilities. The proposed YOLOv7-CHS not only improves signal recognition accuracy but also reduces model Params and computational complexity, achieving a lightweight model with promising application prospects in the rapid detection and recognition of GPS interference sources in civil aviation.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-11-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/9927636","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142641965","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Support Vector Machines Based Mutual Interference Mitigation for Millimeter-Wave Radars","authors":"Mingye Yin,&nbsp;Bo Feng,&nbsp;Jizhou Yu,&nbsp;Liya Li,&nbsp;Yanbing Li","doi":"10.1049/2024/5556238","DOIUrl":"https://doi.org/10.1049/2024/5556238","url":null,"abstract":"<div>\u0000 <p>With the intelligent development of vehicles, the number of vehicles equipped with millimeter-wave (mmWave) radars is increasing, and the possibility of interference between radars is rising dramatically. In automatic driving, it will be common for target detection to be affected by multiple interfering radars. Addressing the mutual interference challenges, an adaptive interference detection method based on support vector machines (SVMs) is proposed. First, a window selection is performed on the received signal and features describing the difference between the normal signal and the interference are extracted. Then, we use a nonlinear SVM to distinguish between the interference and the normal signal. After completing the localization of the interference, we use an autoregressive (AR) prediction model to reconstruct the target echo signal. Results from both multiple interference simulation scenarios and real experimental scenarios show that the accuracy of interference localization and the effect of interference mitigation of the proposed method outperforms the mainstream methods.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-11-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/5556238","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142641418","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Radio Map Reconstruction With Adaptive Spatial Feature Learning","authors":"Jie Yang,&nbsp;Wenbin Guo","doi":"10.1049/2024/7090832","DOIUrl":"https://doi.org/10.1049/2024/7090832","url":null,"abstract":"<div>\u0000 <p>Radio map reconstruction is a fundamental problem of great relevance in numerous real-world applications, such as network planning and fingerprint localization. Sampling the complete radio map is prohibitively costly in practice and difficult to achieve. Such methods for reconstructing radio maps from a subset of measurements are now gaining additional attention. In this paper, we first explore the spatial features of signals on the radio map and formulate the reconstruction problem as an optimization problem with feature penalties. Then, we propose an iteration algorithm with spatial feature learning to reconstruct signals on the radio map, which improves the reconstruction accuracy by using an adaptive feature dictionary. Numerical examples are given to demonstrate the viability and performance of our method at last.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/7090832","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142555518","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Low-Complexity Expectation Propagation Detector for OTFS","authors":"Xumin Pu,&nbsp;Zhinan Sun,&nbsp;Wanli Wen,&nbsp;Qianbin Chen,&nbsp;Shi Jin","doi":"10.1049/2024/3256977","DOIUrl":"https://doi.org/10.1049/2024/3256977","url":null,"abstract":"<div>\u0000 <p>In this paper, we propose a low-complexity expectation propagation (EP) detector for orthogonal time frequency space (OTFS) system with practical rectangular waveforms. In the high-mobility scenario, OTFS is becoming a potential scheme for the sixth-generation (6G) wireless communication system. However, the large size of the effective delay-Doppler (DD) domain channel matrix brings unbearable computational complexity to the signal detection algorithm based on the matrix inversion. We propose a low-complexity EP detector based on the sparsity and the block circulant structure of the effective channel covariance matrix in the DD domain. The proposed algorithm only requires log-linear complexity. In addition, simulation results show that the proposed algorithm not only has the advantage of low complexity but also has good performance, which achieves a tradeoff between performance and complexity.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-10-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/3256977","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142525535","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"One-Bit Distributed Sparse Spectrum Sensing Based on the DQA-ZA-LMS and DQA-RZA-LMS Algorithms Over Adaptive Networks","authors":"Ehsan Mostafapour,&nbsp;Changiz Ghobadi,&nbsp;Javad Nourinia,&nbsp;Ramin Borjali Navesi","doi":"10.1049/2024/9622167","DOIUrl":"https://doi.org/10.1049/2024/9622167","url":null,"abstract":"<div>\u0000 <p>In this paper, we proposed the distributed quantization and sparsity aware zero attracting least mean square (DQA-ZA-LMS) and its reweighted version (DQA-RZA-LMS) algorithms that can perform sparse spectrum sensing with the lowest power possible. The usage of the quantization aware diffusion adaptive networks has recently been proposed and they can be used in many possible mobile communicative applications. The sparsity aware feature of the proposed algorithm can help the network to track and estimate sparse random vectors that are shown to be the case with the spectrum of the new generation wireless communication systems such as 4G, 5G, 6G, and beyond. The spectrum sensing is considered in this paper to be performed by small cell eNode Bs (SC-eNBs) for the 4^th generation long term evolution (LTE) and the next generation eNB (ng-eNB) networks for the 5^th and 6^th generation mobile communication systems that are scattered in an area collecting distributed quantized data from the environment and working collaboratively to estimate the sparse spectrum vectors. Our findings show that in comparison with the nonquantized version of the distributed ZA-LMS (DZA-LMS) and distributed regularized ZA-LMS (DRZA-LMS) algorithms, our proposed schemes perform considerably well using the quantized data and also reduce power consumption.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-10-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/9622167","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142525019","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Effect of Antenna Place Codes for Reducing Sidelobes of SIAR and Frequency Diverse Array Sensors","authors":"Pourya Yaghoubi Aliabad,&nbsp;Hossein Soleimani,&nbsp;Mohammad Soleimani","doi":"10.1049/2024/9458494","DOIUrl":"https://doi.org/10.1049/2024/9458494","url":null,"abstract":"<div>\u0000 <p>Synthetic impulse and aperture radar (SIAR) is a technique that frequency diverse array (FDA) radars can imply in practice, thus overcoming some of their challenges. SIAR radars, used in various fields like transportation and defense, can detect the range, azimuth angle, elevation angle, and Doppler of the target with their 4D-matched filter and a single receiver. However, the challenge of high-amplitude sidelobes is a significant concern for researchers. They have attempted to reduce it through various approaches, including frequency code, range–angle coupling, and range–Doppler coupling, to accurately identify target characteristics. This paper presents the antenna place code (AP code) parameter as a significant factor in minimizing sidelobe amplitudes. The parameter specifies that, rather than having all antennas active, a certain number of antennas are active in each pulse repetition interval (PRI) to achieve a lower sidelobe. Researchers have found that using AP codes can effectively lower the amplitude of the range–angle sidelobe, the range–Doppler sidelobe, error coupling, the repetition of sidelobe strands, and the output of angle error for different target angles. All studies are conducted on a linear array for simplicity. The output of various AP codes is compared to the previously common uniform array.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-10-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/9458494","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142451762","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Variational Bayesian Truncated Adaptive Filter for Uncertain Systems with Inequality Constraints","authors":"Tianli Ma,&nbsp;Rong Zhang,&nbsp;Song Gao,&nbsp;Hong Li,&nbsp;Yang Zhang","doi":"10.1049/2024/3809689","DOIUrl":"https://doi.org/10.1049/2024/3809689","url":null,"abstract":"<div>\u0000 <p>In this paper, a variational Bayesian (VB) truncated adaptive filter for uncertain systems with inequality constraints is proposed. By choosing the skew-<i>t</i> and inverse Wishart distributions as the prior information of the measurement noise and predicted error covariance matrix, the state vector, the predicted error covariance matrix, and noise parameters are inferred and approximated by using the VB method. To achieve the inequality-constrained estimation, the constrained state is computed by truncating the probability density function (PDF) of the estimated state after the variational update stage; the mean and covariance of the constrained state are the first and second moments of the truncated PDF. Considering the model uncertainties where the system dynamics are unpredictable, a multiple model VB truncated adaptive filter is proposed in the interacting multiple model framework. The performances of the proposed algorithms are evaluated via the target tracking simulations and the robot positioning experiments. Results show that the proposed algorithms improve estimation accuracy compared with the existing adaptive filters when the states suffer inequality constraints.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/3809689","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142449179","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Novel Approach of Optimal Signal Streaming Analysis Implicated Supervised Feedforward Neural Networks","authors":"Farhan Ali,&nbsp;He Yigang","doi":"10.1049/2024/2819057","DOIUrl":"https://doi.org/10.1049/2024/2819057","url":null,"abstract":"<div>\u0000 <p>The analysis and interpretation of enormous amounts of data generated by 5G networks present several challenges related to noise, precision, and feasibility validation. Therefore, this study aims to evaluate the effectiveness of channel equalisation in the network and enhance it by distributing signals over all subcarriers and symbols. The error-free signal received ensures the reliable transmission of signals in the network connection. These simulations were undertaken to fulfil the needs of and adapt the transmission properties according to the specific conditions of the channel. The dataset consists of artificially generated radio waves to train signals through neural networks (NNs) and machine learning algorithms to detect errors properly. The primary objective is to achieve optimal signal performance. In this regard, an artificial neural network (ANN) was initially employed, explicitly utilising the back-propagation technique and a feedforward multilayer perceptron (MLP). In addition, the signals were subjected to train using a real-time simulator, employing feedforward neural network and support vector machine (SVM) to validate the proposed methodology. Feedforward MLP achieved the highest performance in simulations compared to SVM. The scheme is promising to achieve optimal signal performance in real-time.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/2819057","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142404436","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Energy Sharing and Performance Bounds in MIMO DFRC Systems: A Trade-Off Analysis","authors":"Ziheng Zheng,&nbsp;Xiang Liu,&nbsp;Tianyao Huang,&nbsp;Yimin Liu,&nbsp;Yonina C. Eldar","doi":"10.1049/2024/8852387","DOIUrl":"https://doi.org/10.1049/2024/8852387","url":null,"abstract":"<div>\u0000 <p>It is a fundamental problem to analyze the performance bound of multiple-input multiple-output dual-functional radar-communication systems. To this end, we derive a performance bound on the communication function under a constraint on radar performance. To facilitate the analysis, in this paper, we consider a simplified situation where there is only one downlink user and one radar target. We analyze the properties of the performance bound and the corresponding waveform design strategy to achieve the bound. When the downlink user and the radar target meet certain conditions, we obtain analytical expressions for the bound and the corresponding waveform design strategy. The results reveal a tradeoff between communication and radar performance, which is essentially caused by the energy sharing and allocation between radar and communication functions of the system.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-09-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/8852387","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142275039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A Labeled Multi-Bernoulli Filter Based on Maximum Likelihood Recursive Updating","authors":"Yuhan Song,&nbsp;Han Shen-Tu,&nbsp;Junhao Lin,&nbsp;Yizhen Wei,&nbsp;Yunfei Guo","doi":"10.1049/2024/1994552","DOIUrl":"https://doi.org/10.1049/2024/1994552","url":null,"abstract":"<div>\u0000 <p>A labeled multi-Bernoulli filter is used to obtain estimates of the identities and states of targets in complex environments. However, when tracking multiple targets in dense clutters, the computational complexity of the traditional labeled multi-Bernoulli filter will increase exponentially. A labeled multi-Bernoulli tracking algorithm based on maximum likelihood recursive update is proposed, which can reduce the computational scale while maintaining tracking accuracy. Specifically, when performing posterior estimation, a maximum likelihood recursive update method is proposed to replace the complete enumeration, truncated enumeration, or sampling enumeration methods used in many traditional methods. Furthermore, combined with the Gaussian mixture technique, a maximum likelihood recursive updating labeled multi-Bernoulli tracking algorithm is constructed. Simulation results demonstrated that the proposed filter obtained a good balance between the tracking accuracy and computational efficiency.</p>\u0000 </div>","PeriodicalId":56301,"journal":{"name":"IET Signal Processing","volume":"2024 1","pages":""},"PeriodicalIF":1.1,"publicationDate":"2024-09-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/2024/1994552","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142170139","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}