Iet Radar Sonar and Navigation最新文献

{"title":"Interrupted sampling repeater jamming suppression based on multiple extended complex-valued convolutional auto-encoders","authors":"Yunyun Meng,&nbsp;Lei Yu,&nbsp;Yinsheng Wei","doi":"10.1049/rsn2.12568","DOIUrl":"10.1049/rsn2.12568","url":null,"abstract":"<p>Interrupted sampling repeater jamming (ISRJ) with flexible modulation parameters and coherent processing gain seriously threatens the radar detection system. The jamming suppression and target detection performance of existing anti-jamming methods are limited by strong noise and jamming signals. An ISRJ suppression method combining multiple extended complex-valued convolutional auto-encoders (CVCAEs) and compressed sensing (CS) reconstruction is proposed. For the different tasks of parameter estimation and signal denoising, the extended CVCAEs including a complex-valued convolutional shrinkage network (CVCSNet) and a complex-valued UNet (CVUNet) are developed. Based on the time-domain discontinuity of ISRJ signals, the CVCSNet is first used to directly estimate the parameters representing signal components and extract jamming-free signals from received signals. Then, the extracted signals are denoised using the CVUNet. After that, relying on the denoised signals and the frequency sparsity of de-chirped target signals, a CS model is established and solved to recover complete target signals for jamming suppression. Utilising the advantages of deep neural networks in weak feature extraction and signal representation, the CVCSNet and CVUNet can effectively improve the signal extraction accuracy and alleviate the limitation of noise on target signal reconstruction. Experimental results verify that the proposed method has superior ISRJ suppression performance and is robust to varying signal-to-noise ratios, jamming-to-signal ratios and jamming parameters.</p>","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"18 8","pages":"1274-1290"},"PeriodicalIF":1.4,"publicationDate":"2024-04-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.12568","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140591412","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Track initialisation for multiple formations based on neutrosophic Hough transform","authors":"Yang Penggang, Wang Kun, Feng Guangdong","doi":"10.1049/rsn2.12567","DOIUrl":"https://doi.org/10.1049/rsn2.12567","url":null,"abstract":"Track crossing is a major issue in the initialisation of multiple-flight trajectories. To solve this problem, the authors propose a track initialisation algorithm. It uses characteristics of formation flight to find centroids of each formation with DBSCAN algorithm. Then, it initialises the track based on the centroid. The author use a Neutrosophic Hough Transform (NHT) method to improve accuracy and computational speed. That helps address errors caused by the approximation of straight lines between true points resulting from the clustering algorithm. The authors made three experiments using track initialisation data from two flight formations with five target aircraft each, over a span of three frames. NHT, Fuzzy HT, Improved Hough Transform (HT) and HT are compared. Results revealed that the average runtime of NHT was 10.2153 s. The F-measure of NHT was 100.00%, while that of Fuzzy HT was 9.8347 s. The F-measure of Fuzzy HT was 80.00%. The Improved HT was 12.0723 s. The F-measure of Improved HT was 11.76% and HT was 13.783 s. And the F-measure of HT was 6.87%. The authors lost some computation speed to achieve higher prediction accuracy. The accuracy of the NHT is higher than other methods.","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"298 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-04-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140591317","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Open-set recognition of compound jamming signal based on multi-task multi-label learning","authors":"Yihan Xiao,&nbsp;Rui Zhang,&nbsp;Xiangzhen Yu,&nbsp;Yilin Jiang","doi":"10.1049/rsn2.12561","DOIUrl":"10.1049/rsn2.12561","url":null,"abstract":"<p>In the increasingly intricate electromagnetic environment, the radar receiver may simultaneously encounter multiple intentional or unintentional jamming signals, which results in temporal and spectral overlap of received signals and forms a composite jamming signal. The nature and extent of interference contained in the received signal are often unknown, while they significantly affect the accuracy of radar detection. AnOpen-Set Compound Jamming Signal Recognition Framework based on Multi-Task Multi-Label (MTML-OCJR) is proposed. Based on the time–frequency characteristic of compound jamming signals, the proposed framework employs multi-label classification to identify components of compound jamming signals while incorporating an unknown signal detection task into the classification process. Time–frequency image reconstruction combined with extreme value model estimation is used to detect unknown types of jamming signals, enabling simultaneous signal recognition and anomaly detection. The obtained results show that the proposed approach has superior recognition performance for composite jamming signals in closed-set environments and high anomaly detection ability for unknown signals in open-set environments. This method has the potential to significantly enhance the effectiveness and reliability of jamming systems in battlefield scenarios.</p>","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"18 8","pages":"1235-1246"},"PeriodicalIF":1.4,"publicationDate":"2024-03-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.12561","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140591329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Dual-labelled multi-Bernoulli filter based on specific emitter identification","authors":"Xin Guan, Yu Lu","doi":"10.1049/rsn2.12558","DOIUrl":"https://doi.org/10.1049/rsn2.12558","url":null,"abstract":"In complex electromagnetic environments, airborne passive bistatic radar encounters the challenge of associating emitters with measurements for multi-target tracking. The authors propose a solution based on specific emitter identification technology. Firstly, generative adversarial networks (GANs) are utilised to extract and classify emitter signals using radio frequency fingerprint (RFF) features. The classification results are then used to construct a set of emitter labels for pre-processing the measurement data. Subsequently, the pre-processed measurement data set is input into the labelled multi-Bernoulli filter framework, which is extended to a dual-labelled (target label and emitter label) multi-Bernoulli filter. This filter jointly predicts and updates the multi-target posterior density, enabling the estimation of multi-target trajectories. The effectiveness of the proposed algorithm is validated using two experiments. The results demonstrate that the GAN based on RFF features effectively identifies emitter signals. Moreover, the dual-labelled multi-Bernoulli filter, based on specific emitter identification, accurately estimates multi-target trajectories using measurement data from an airborne passive radar of the multi-transmit single-receive type. This approach provides a novel and effective solution to the multi-target tracking problem in complex electromagnetic environments.","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"23 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140325074","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Adaptive soft threshold transformer for radar high-resolution range profile target recognition","authors":"Siyu Chen,&nbsp;Xiaohong Huang,&nbsp;Weibo Xu","doi":"10.1049/rsn2.12563","DOIUrl":"10.1049/rsn2.12563","url":null,"abstract":"<p>Radar High-Resolution Range Profile (HRRP) has great potential for target recognition because it can provide target structural information. Existing work commonly applies deep learning to extract deep features from HRRPs and achieve impressive recognition performance. However, most approaches are unable to distinguish between the target and non-target regions in the feature extraction process and do not fully consider the impact of background noise, which is harmful to recognition, especially at low signal-to-noise ratios (SNR). To tackle these problems, the authors propose a radar HRRP target recognition framework termed Adaptive Soft Threshold Transformer (ASTT), which is composed of a patch embedding (PE) layer, ASTT blocks, and Discrete Wavelet Patch Merging (DWPM) layers. Given the limited semantic information of individual range cells, the PE layer integrates nearby isolated range cells into semantically explicit target structure patches. Thanks to its convolutional layer and attention mechanism, the ASTT blocks assign a weight to each patch to locate the target areas in the HRRP while capturing local features and constructing sequence correlations. Moreover, the ASTT block efficiently filters noise features in combination with a soft threshold function to further enhance the recognition performance at low SNR, where the threshold is adaptively determined. Utilising the reversibility of the discrete wavelet transform, the DWPM layer efficiently eliminates the loss of valuable information during the pooling process. Experiments based on simulated and measured datasets show that the proposed method has excellent target recognition performance, noise robustness, and small-scale range shift robustness.</p>","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"18 8","pages":"1260-1273"},"PeriodicalIF":1.4,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.12563","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140324739","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Full-duplex capable multifunction joint radar–communication–security transceiver with pseudonoise–orthogonal frequency-division multiplexing mixture waveform","authors":"Jaakko Marin,&nbsp;Micael Bernhardt,&nbsp;Taneli Riihonen","doi":"10.1049/rsn2.12562","DOIUrl":"10.1049/rsn2.12562","url":null,"abstract":"<p>The authors investigate the performance of an original multifunction system with two in-band full-duplex capable joint radar, communications and security (JRCS) transceivers in the presence of an eavesdropper. The system concept can be generalised to a network of more than two JRCS transceivers and multiple eavesdroppers, despite the present study focusing on the three-node scenario. By combining a bandlimited pseudonoise waveform with a data-containing orthogonal frequency-division multiplexing (OFDM) waveform, the authors are able to ensure a certain jamming-to-signal power ratio (JSR) at the eavesdropper, whilst ideal synchronisation ensures that jamming causes no deterioration to their own data transfer or radar sensing performance as it is possible to remove just the known pseudonoise waveform. To validate the system, the authors investigate through simulations the OFDM symbol error rates of all the receivers, radar target signal-to-interference-plus-noise power ratios as well as receiver operating characteristic curves, and eavesdropper's detection signal-to-noise power ratios through two-branch receiver cross-correlation. The results show that already a very low JSR of −20 dB can improve physical-layer security without a significant increase in friendly symbol error rate or deterioration in radar performance. Additionally, other full-duplex transceivers potentially occupying the same radio resources improve the secrecy even further.</p>","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"18 7","pages":"1055-1067"},"PeriodicalIF":1.4,"publicationDate":"2024-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.12562","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140324946","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Guest Editorial: Radar systems and processing methods for space situational awareness","authors":"Peter Knott,&nbsp;Alberto Moreira,&nbsp;Braham Himed","doi":"10.1049/rsn2.12566","DOIUrl":"10.1049/rsn2.12566","url":null,"abstract":"&lt;p&gt;Satellites and the services they provide are indispensable to our society: Communication, Navigation, Remote Sensing, Surveillance, and Reconnaissance—all of these applications benefit significantly from the support of an ever-growing network of ubiquitous sub-systems in orbit. Although space seems almost infinite and the population comparatively small, increasingly frequent orbital overlaps, conjunctions and sometimes even collisions clearly show us how vulnerable this environment is. Due to the increasing number of satellites and the associated increase in space debris (e.g. man-made remnants of rocket launches, defective payloads, or their fragments) and the growing threat of attacks in military conflicts, protecting this critical infrastructure is becoming an increasingly important task.&lt;/p&gt;&lt;p&gt;Space situational awareness (SSA) is the ability to monitor activities, objects, and events in outer space. It involves detecting, imaging, tracking, and analysing the positions, trajectories, and characteristics of satellites, space debris, and other objects in space. Due to the laws of physics, the precise assessment and cataloguing of such data also allows for a look into the future and can predict the position of objects over an extended period. Thus, one main purpose of SSA is to enhance the safety, security, and sustainability of space activities by providing essential information, for example, on potential collisions and on the purpose of satellites.&lt;/p&gt;&lt;p&gt;Among the various sensors used for SSA, radar sensors hold a particularly important position. The primary advantages of radars in this context are that they do not need an external source of illumination, can detect the smallest debris over long ranges, accurately track objects even against the bright daylight sky and actively measure the distance as well as target motion. Imaging radars using inverse synthetic aperture radar (ISAR) techniques can provide a high-resolution image of an object and reconstruct a three-dimensional representation of its shape and features using either a bistatic, multistatic or radargrammetric system configuration.&lt;/p&gt;&lt;p&gt;In this first Special Issue of &lt;i&gt;IET Radar, Sonar and Navigation&lt;/i&gt; on ‘Radar Systems and Processing Methods for SSA’, we are presenting eight articles covering the following topics.&lt;/p&gt;&lt;p&gt;The paper, ‘High-resolution ISAR imaging of satellites in space’ by S. Anger, M. Jirousek, et al., comprehensively illustrates the technological steps for the construction and successful operation of advanced radar-based space surveillance. Besides the basic description of the experimental system design based on pulse radar technology, this paper outlines a useful theory for ISAR imaging of objects in space, together with relevant imaging parameters, calibration and error correction. All relevant processing steps, necessary for very high-resolution imaging of satellites in practice, are introduced and verified by simulation as well as measurement results.&lt;/p&gt;","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"18 4","pages":"541-543"},"PeriodicalIF":1.7,"publicationDate":"2024-03-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.12566","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140324860","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Time transfer via single-record TDoA measurements of GNSS satellites using direct cross-correlation and relative pilot code phases","authors":"Erik Busley, Timotej Žuntar, Jörg Borgmann, Michael Krist","doi":"10.1049/rsn2.12557","DOIUrl":"https://doi.org/10.1049/rsn2.12557","url":null,"abstract":"Radar systems are evolving towards distributed receiver networks. As individual stations might be separated too far to install a cable link, novel methods are required to synchronise individual data records in the time domain. State-of-the-art GNSS receivers disciplining a highly stable oscillator are able to output a timing signal with several nanosecond accuracy solely using non-proprietary signals. However, they typically require a stable environment and become a major cost factor for receiver networks with a high number of nodes. A method is presented to passively synchronise data records via GNSS raw signals in a single record requiring only a GNSS antenna, an analogue-to-digital converter and computation hardware. The clock bias is estimated via the common view method with either full raw signal correlation or software-based code correlation of individual signals from the GPS, Galileo and BeiDou constellation with sub-nanosecond precision.","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"11 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140200789","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"A novel distributed bearing-only target tracking algorithm for underwater sensor networks with resource constraints","authors":"Wei Zhao,&nbsp;Xuan Li,&nbsp;Zhouqi Pang,&nbsp;Chengpeng Hao","doi":"10.1049/rsn2.12554","DOIUrl":"10.1049/rsn2.12554","url":null,"abstract":"<p>Underwater sensor networks hold immense potential for advancing the field of underwater target tracking, yet they encounter significant resource constraints stemming from energy storage and communication methods. In order to balance tracking accuracy and energy consumption, the authors present a distributed bearing-only target tracking algorithm that can be used in underwater sensor networks with resource constraints. Anchored in the diffusion cubature information filter framework, this algorithm achieves fusion for non-linear bearing measurements and state estimation. During the incremental update stage, individual nodes leverage the Posterior Cramer-Rao Lower Bound as a metric for tracking performance. Subsequently, a strategy for selecting neighbouring nodes is introduced, ensuring tracking accuracy while efficiently kerbing energy consumption. In the diffusion update stage, a multi-threshold event triggering mechanism is employed to partially diffuse the intermediate estimation. Additionally, an adaptive convex combination weight is proposed for cases involving partial diffusion. Through theoretical analysis, the asymptotic unbiasedness and convergence of the algorithm have been proven. Through Monte Carlo simulation experiments, the authors verify that the algorithm is superior to existing algorithms. Furthermore, the algorithm significantly reduces energy consumption in information interaction, minimising tracking accuracy loss.</p>","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"18 7","pages":"1161-1177"},"PeriodicalIF":1.4,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.12554","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140200786","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Underdetermined blind source separation based on third-order cumulant and tensor compression","authors":"Weilin Luo, Xiaobai Li, Hongbin Jin, Hao Li, Kai Yuan, Ruijuan Yang","doi":"10.1049/rsn2.12553","DOIUrl":"https://doi.org/10.1049/rsn2.12553","url":null,"abstract":"A method for Underdetermined Blind Source Separation is proposed using third-order cumulants and tensor compression. To effectively suppress symmetrical distributed noise, the third-order cumulant is considered. Additionally, the complexity of high-dimensional tensors can be reduced through high order singular value decomposition (HOSVD) for compression purposes. The method begins by calculating the third-order cumulant tensor for whitening signals at different time delays, and then stacks several cumulants into a fourth-order tensor. The HOSVD decomposition is applied to the fourth-order tensor, compressing the high-dimensional tensor into a low-dimensional core tensor. Next, the core tensor is further decomposed using the canonical polyadic decomposition, and the resulting factor matrices are fused to obtain an estimation of the mixed matrix. Finally, leveraging the signal independence, a matrix diagonalisation method is employed to recover the source signals. Theoretical analysis and simulation results demonstrate that the proposed method effectively suppresses the influence of Gaussian noise, reduces computational complexity, and saves computational time. Moreover, compared with five representative approaches, the proposed method achieves superior separation results. Specifically, for the 3 × 4 mixed model with a signal-to-noise ratio of 20 dB, the average relative error of speech signal and radio signal are −11.02 and −6.8 dB respectively.","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"2015 1","pages":""},"PeriodicalIF":1.7,"publicationDate":"2024-03-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"140200791","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}