Iet Radar Sonar and Navigation最新文献

A Robust Stochastic Modelling Approach for Tight Integration of Precise Point Positioning and Ultra-Wide Band

IF 1.4 4区管理学

Iet Radar Sonar and Navigation Pub Date : 2025-03-14 DOI: 10.1049/rsn2.70015

Tonghui Shen, Changsheng Cai, Wenping Jin

{"title":"A Robust Stochastic Modelling Approach for Tight Integration of Precise Point Positioning and Ultra-Wide Band","authors":"Tonghui Shen, Changsheng Cai, Wenping Jin","doi":"10.1049/rsn2.70015","DOIUrl":"https://doi.org/10.1049/rsn2.70015","url":null,"abstract":"An accurate stochastic model is essential for achieving high-accuracy positioning solutions in the global navigation satellite system (GNSS) precise point positioning (PPP)/ultra-wide band (UWB) tightly coupled (TC) integration. Conventionally, a priori variances are used in the PPP/UWB TC integration to determine the weights of observations. However, a priori variances are difficult to obtain in complex environments since the stochastic characteristics of different observations depend heavily on environmental conditions. By contrast, the variance component estimation (VCE) method can provide a more accurate stochastic model by estimating the measurement uncertainties of different types of observations. Nevertheless, the VCE is susceptible to measurements' outliers and low redundancy in complex observation environments. To address these issues, a robust stochastic modelling approach for PPP/UWB TC integration is proposed by optimising the VCE with a robust estimation strategy and an adaptive moving window filter technique. Two kinematic experiments are conducted in signal-obstructed environments to validate the stochastic modelling approach. Results demonstrate that the three-dimensional (3D) positioning accuracy in the PPP/UWB TC integration is improved by over 47% after VCE optimisation. Compared to the a priori variance-based stochastic model, the robust stochastic modelling approach improves the 3D positioning accuracy by over 27%.","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"19 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-03-14","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.70015","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143622585","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}

引用次数: 0

Radar signal deinterleaving in open-set environments based variational autoencoder with probabilistic ladder structure

IF 1.4 4区管理学

Iet Radar Sonar and Navigation Pub Date : 2025-03-11 DOI: 10.1049/rsn2.12697

Huibo Sun, Kai Xie

引用次数: 0

Rain Clutter Modelling and Performance Assessment of Road Traffic Surveillance Radars

IF 1.4 4区管理学

Iet Radar Sonar and Navigation Pub Date : 2025-03-11 DOI: 10.1049/rsn2.70008

Hai-Long Su, Xiao-Jun Zhang, Yi-Han Li, You-Heng Wang, Peng-Jia Zou, Peng-Lang Shui

{"title":"Rain Clutter Modelling and Performance Assessment of Road Traffic Surveillance Radars","authors":"Hai-Long Su, Xiao-Jun Zhang, Yi-Han Li, You-Heng Wang, Peng-Jia Zou, Peng-Lang Shui","doi":"10.1049/rsn2.70008","DOIUrl":"https://doi.org/10.1049/rsn2.70008","url":null,"abstract":"Millimetre-wave road traffic surveillance radars are used for vehicle detection and tracking. Under rainy conditions, rain attenuation and rain backscatter severely degrade the vehicle detection performance of radars. In this paper, based on a big database of rain clutter collected by two radars at different rainfall levels, rain clutter modelling and the assessment of the vehicle detection ability of radars under rainy conditions are investigated. As the first contribution, the clutter-to-noise ratio (CNR) and signal-to-clutter-noise ratio (SCNR) of the road traffic surveillance radar under rainy conditions are derived as functions of radial distance, based on the rain attenuation and backscatter models. The derived formulas highly accord with the measured CNR change of radars under rainy conditions, which can be used to evaluate radar performance and optimise the radar operating mode. As the second contribution, a range-varying compound-Gaussian model (CGM) with a clutter map cell partition is introduced to model rain clutter with range-varying statistics, and a best-type selection method of amplitude distributions is proposed. Based on the analysis of a big database of rain clutter at different rainfall levels, the range-varying CGMs with gamma and lognormal textures are recommended to model rain clutter of millimetre-wave road traffic surveillance radars.","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"19 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-03-11","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.70008","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143594940","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}

引用次数: 0

Bayesian Radar Cosplace: Directly estimating location uncertainty in radar place recognition

IF 1.4 4区管理学

Iet Radar Sonar and Navigation Pub Date : 2025-03-04 DOI: 10.1049/rsn2.70002

Suyash Agarwal, Jianhao Yuan, Paul Newman, Daniele De Martini, Matthew Gadd

{"title":"Bayesian Radar Cosplace: Directly estimating location uncertainty in radar place recognition","authors":"Suyash Agarwal, Jianhao Yuan, Paul Newman, Daniele De Martini, Matthew Gadd","doi":"10.1049/rsn2.70002","DOIUrl":"https://doi.org/10.1049/rsn2.70002","url":null,"abstract":"Trust and explainability in localisation systems can be greatly helped by estimating a calibrated uncertainty. In this work, we argue for the first time that for this, it is best to express uncertainty in the location estimate directly rather than indirectly in the ‘noisiness’ or ambiguity of the data sample. Therefore, in this work, through a robust classification-based model, we not only identify the most probable place but also provide a measure of confidence or uncertainty associated with the prediction of the place itself—in contrast to existing approaches where uncertainty values are produced with the same dimension as the encoded feature. We specifically prove the utility of this new formulation on CosPlace, a state-of-the-art Geolocalisation system. Uncertainty is learnt by transforming Cosplace into an uncertainty-aware neural network. To validate the effectiveness of our approach, we conduct extensive experiments using the Oxford Radar RobotCar Dataset, where we find that the backbone features learnt in the uncertainty-aware setting result in better place recognition performance than vanilla Cosplace. Furthermore, by using it as a score to reject putative localisation results, we show that our uncertainty is well-calibrated to place recognition accuracy—more so than two existing systems in uncertainty-aware radar place recognition.","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"19 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-03-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.70002","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143554443","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}

引用次数: 0

Sparse Bayesian learning using hierarchical synthesis prior for STAP

IF 1.4 4区管理学

Iet Radar Sonar and Navigation Pub Date : 2025-02-26 DOI: 10.1049/rsn2.70001

Junxiang Cao, Tong Wang, Weichen Cui

{"title":"Sparse Bayesian learning using hierarchical synthesis prior for STAP","authors":"Junxiang Cao, Tong Wang, Weichen Cui","doi":"10.1049/rsn2.70001","DOIUrl":"https://doi.org/10.1049/rsn2.70001","url":null,"abstract":"Space–time adaptive processing (STAP) can effectively detect moving targets in the background of ground clutter, but the performance will drop sharply when the training samples are limited. In this paper, to improve the clutter suppression performance when the training samples are limited, the authors propose a novel STAP algorithm based on sparse Bayesian learning (SBL) using a hierarchical synthesis prior. Firstly, we construct a novel three-level hierarchical synthesis prior (HSP) model, which promotes the sparsity more significantly than traditional priors used in SBL. Secondly, in the framework of type-II maximum likelihood approach, a novel iterative update criterion for hyperparameters is derived. Thirdly, in order to reduce the computational burden, the authors design a novel local space–time dictionary to transform the full-dimensional clutter spectrum recovery problem into a local clutter spectrum recovery problem. Numerical results with both simulated and measured data demonstrate the excellent performance and relatively high computational efficiency of the proposed method.","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"19 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.70001","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143497175","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}

引用次数: 0

Open-DS: An Open-Set Modulation Recognition Method for Low Probability of Interception Radar Emitters Based on Dictionary Similarity

IF 1.4 4区管理学

Iet Radar Sonar and Navigation Pub Date : 2025-02-25 DOI: 10.1049/rsn2.70007

Gangyin Sun, Shiwen Chen, Chaopeng Wu, Li Zhang, Haikun Fang

{"title":"Open-DS: An Open-Set Modulation Recognition Method for Low Probability of Interception Radar Emitters Based on Dictionary Similarity","authors":"Gangyin Sun, Shiwen Chen, Chaopeng Wu, Li Zhang, Haikun Fang","doi":"10.1049/rsn2.70007","DOIUrl":"https://doi.org/10.1049/rsn2.70007","url":null,"abstract":"The recognition of radar emitters modulation in an open-set scenario presents a challenging task, particularly when identifying unknown modulation. This paper proposes a dictionary similarity based method for low intercept probability radar signal open-set modulation recognition (OMR), designed to address the unknown modulation in open-set scenarios. First, deep features of the input 1-D signal are extracted, and a random Fourier transform is applied to map the signal into a high-dimensional space, thereby converting the nonlinear feature optimisation problem into a linear optimisation problem. Next, an inter-class discreteness (ICD) module and an intra-class similarity (ICS) module are designed. Based on the Hilbert-Smith independence criterion, the correlation between features is quantified, and the quantitative values of ICD and ICS are used as loss functions to constrain the network's learning process. This approach effectively enhanced the representational power of the class dictionaries and significantly improved the model’s overall performance. Experimental results demonstrate that the proposed strategy successfully extracts high-dimensional feature prototypes, achieving high accuracy in closed-set recognition while effectively performing open-set recognition tasks.","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"19 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-02-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.70007","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143481535","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}

引用次数: 0

WaveMic: Speech recognition of Chinese digit numbers from radio signals

IF 1.4 4区管理学

Iet Radar Sonar and Navigation Pub Date : 2025-02-21 DOI: 10.1049/rsn2.70000

Shengchang Lan, Changhao Yang, Beijia Liu, Juwen Chen

{"title":"WaveMic: Speech recognition of Chinese digit numbers from radio signals","authors":"Shengchang Lan, Changhao Yang, Beijia Liu, Juwen Chen","doi":"10.1049/rsn2.70000","DOIUrl":"https://doi.org/10.1049/rsn2.70000","url":null,"abstract":"In recent years, the use of millimetre wave radio signals for speech recognition has rapidly developed. The absence of high-frequency components resulting from the material vibration constraints of fully viewed indoor objects has undermined the recognition accuracy in this field. This paper presents a new solution to the Chinese digits speech recognition problem by reconstructing the high-frequency harmonic and non-harmonic components with the radio signals received by millimetre wave radar sensors. A time–frequency analysis was conducted to convert the phase variations extracted from the radar I/Q signals to spectrograms. An improved threshold strategy was used to enhance the harmonic components on the spectrogram. Subsequently, a CycleGAN-based network was constructed to recover non-harmonic components on the spectrograms. An evaluation experiment was performed with a 77-GHz frequency modulated continuous wave radar sensor to use the induced vibrations of aluminium foils, glass, and anti-static bags to recognise the speeches of standard Chinese digit numbers (0–9). The F1 score in the speech recognition experiment reached 96.6%, with a micro average accuracy exceeding 98.3%. These results show that the proposed method can improve recognition accuracy by generating finer signatures from radio signals.","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"19 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.70000","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143466172","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}

引用次数: 0

Broadband signal DOA estimation based on two-sided correlation transformation using array manifold interpolation

IF 1.4 4区管理学

Iet Radar Sonar and Navigation Pub Date : 2025-02-16 DOI: 10.1049/rsn2.12669

Jun Cao, JiaJun Xiong, Weizhe Xu, Wenxin Qu, Yao Wang, Shuai Liu

{"title":"Broadband signal DOA estimation based on two-sided correlation transformation using array manifold interpolation","authors":"Jun Cao, JiaJun Xiong, Weizhe Xu, Wenxin Qu, Yao Wang, Shuai Liu","doi":"10.1049/rsn2.12669","DOIUrl":"https://doi.org/10.1049/rsn2.12669","url":null,"abstract":"The two-sided correlation transformation (TCT) algorithm is widely used to estimate the direction of arrival (DOA) for broadband signals. However, the traditional TCT algorithm requires DOA pre-estimation, which results in a high computational complexity and poor performance under low signal-to-noise ratio (SNR) conditions. To address these challenges, an improved TCT algorithm based on array manifold interpolation (AMI) is proposed in this paper, which utilised the AMI method to decompose the array manifold matrix and reconstruct the signal covariance matrix. It aims to obtain a DOA-independent focusing transformation matrix, thereby avoiding DOA pre-estimation. The simulation and lake experiment results are compared with the traditional TCT algorithms. It shows that the proposed algorithm can achieve higher DOA estimation accuracy and better angular resolution even in low SNR environments by fully utilising the information within the whole bandwidth of the target while reducing computational complexity.","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"19 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-02-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.12669","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143423562","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}

引用次数: 0

Hybrid polarimetry inverse synthetic aperture radar

IF 1.4 4区管理学

Iet Radar Sonar and Navigation Pub Date : 2025-02-13 DOI: 10.1049/rsn2.70004

Ajeet Kumar, Elisa Giusti, Marco Martorella

{"title":"Hybrid polarimetry inverse synthetic aperture radar","authors":"Ajeet Kumar, Elisa Giusti, Marco Martorella","doi":"10.1049/rsn2.70004","DOIUrl":"https://doi.org/10.1049/rsn2.70004","url":null,"abstract":"The inverse synthetic aperture radar (ISAR) system exploits the movement of the target to form its high-resolution image. Further, the multi-polarisation acquisition in ISAR collects additional information on the target's scattering properties and surface characteristics that help to enhance the imaging capabilities of ISAR. In this study, we suggest a novel multi-polarisation ISAR configuration based on the circular transmit and linear receive (CTLR) combination, namely CTLR hybrid-pol ISAR, for the application of non-cooperative target detection and imaging. The CTLR hybrid-pol ISAR captures sufficient information about the targets to accurately characterise them, and simultaneously overcomes the drawbacks of full-polarimetry (full-pol) ISAR associated with the transmission of two pulses to obtain a single unit of polarimetric back-scattered information. Validation is performed using real ISAR data of a T-72 tank target, collected under the moving and stationary target acquisition and recognition (MSTAR) programme conducted by the Georgia Tech Research Institute. A comparative analysis based on SPAN, entropy, and polarimetric decomposition is carried out between the full-pol ISAR and CTLR hybrid-pol ISAR information. The results conclude that CTLR hybrid-pol ISAR maintains a similar level of information content compared to full-pol ISAR while overcoming its drawbacks.","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"19 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-02-13","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.70004","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143404664","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}

引用次数: 0

Impact of 3D model simplifications on the determination of numerical accuracy of the radar cross-section in aerial target recognition issues

IF 1.4 4区管理学

Iet Radar Sonar and Navigation Pub Date : 2025-02-06 DOI: 10.1049/rsn2.70003

Witold Bużantowicz, Marta Walenczykowska

{"title":"Impact of 3D model simplifications on the determination of numerical accuracy of the radar cross-section in aerial target recognition issues","authors":"Witold Bużantowicz, Marta Walenczykowska","doi":"10.1049/rsn2.70003","DOIUrl":"https://doi.org/10.1049/rsn2.70003","url":null,"abstract":"Method of moments is one of the most useful approaches for radar cross-section (RCS) simulation, allowing, that is, the computation of the scattering of real objects from 3D models. However, it is limited by computer memory and computation time. In this paper, the authors explore the question of the balance between the possible acceptable level of 3D model simplification and the time benefit associated with a decrease in computational overhead due to the reduction of the model geometry complexity. A spatial volume-based RCS characterisation quality index is proposed to help determine the level of simplification to achieve a significant reduction in computation time while maintaining an acceptable level of similarity. The authors present the results of the calculations performed for perfectly conducted sphere 3D models with varying levels of geometry simplification for which a simple analytical solution exists. Furthermore, the results of the computations performed for a generic missile model set are shown. Possible areas of the application of the proposed approach are also considered.","PeriodicalId":50377,"journal":{"name":"Iet Radar Sonar and Navigation","volume":"19 1","pages":""},"PeriodicalIF":1.4,"publicationDate":"2025-02-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1049/rsn2.70003","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143362347","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}

引用次数: 0