Theory and Algorithms for Feedback Particle Filter

反馈粒子滤波器的理论和算法

基本信息

  • 批准号:
    1761622
  • 负责人:
  • 金额:
    $ 37.8万
  • 依托单位:
  • 依托单位国家:
    美国
  • 项目类别:
    Standard Grant
  • 财政年份:
    2018
  • 资助国家:
    美国
  • 起止时间:
    2018-08-01 至 2023-07-31
  • 项目状态:
    已结题

项目摘要

Finding accurate solutions for complex optimization problems and other related challenging mathematical problems is very important in many engineering applications. Some example applications include: target tracking and surveillance where multiple sensor measurements are used to track targets, air traffic management to track airplanes, weather surveillance to track hurricanes, ground mapping, geophysical surveys, remote sensing, autonomous navigation, and robotics. State-of-the-art solution approaches to these problems include the Kalman filter algorithm and its many extensions. However, in practice, such approaches can yield inaccurate and erroneous solutions because of technical issues related to complexity in dynamics and uncertainty. In the past decade, a new class of algorithmic solution approaches to these problems has emerged referred to as the "Feedback Particle Filter". The Feedback Particle Filter can better handle the technical issues related to such complex dynamics and uncertainty. This research will advance the theoretical development and verification of the Feedback Particle Filter algorithm, and lay the groundwork for software tools that will be useful in tracking applications noted above. The project also includes several educational initiatives that seek to engage undergraduate students in entrepreneurship. A major objective of the research concerns the development of optimal control formulations of the feedback particle filter based on optimal transportation theory and mean-field games formalisms. The theoretical research is closely integrated with the work on computational algorithms. The algorithmic objectives pertain to numerical solution of the Poisson equation, convergence analysis of the particle system with finitely many particles, and comparisons with importance sampling-based algorithms. The deliverables include efficient numerical schemes which will be implemented and demonstrated in software.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
在许多工程应用中,寻找复杂优化问题和其他相关的具有挑战性的数学问题的精确解是非常重要的。一些示例应用包括:目标跟踪和监视,其中使用多个传感器测量来跟踪目标,空中交通管理来跟踪飞机,天气监视来跟踪飓风,地面测绘,地球物理调查,遥感,自主导航和机器人。这些问题的最先进的解决方案包括卡尔曼滤波算法及其许多扩展。 然而,在实践中,由于与动态和不确定性的复杂性相关的技术问题,这种方法可能产生不准确和错误的解决方案。 在过去的十年中,出现了一类新的算法解决这些问题的方法,称为“反馈粒子滤波器”。 反馈粒子滤波器可以更好地处理与这种复杂的动态和不确定性相关的技术问题。 这项研究将推进反馈粒子滤波算法的理论发展和验证,并为上述跟踪应用程序中有用的软件工具奠定基础。该项目还包括几项教育举措,旨在让本科生参与创业。 研究的一个主要目标是基于最优运输理论和平均场博弈形式主义的反馈粒子滤波器的最优控制公式的发展。 理论研究与计算算法的研究紧密结合。 算法的目标涉及泊松方程的数值解,收敛性分析的粒子系统与多个粒子,并与重要性抽样为基础的算法进行比较。 该奖项反映了NSF的法定使命,并被认为是值得通过使用基金会的智力价值和更广泛的影响审查标准进行评估的支持。

项目成果

期刊论文数量(9)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Optimal Transportation Methods in Nonlinear Filtering
非线性滤波中的最优传输方法
  • DOI:
    10.1109/mcs.2021.3076391
  • 发表时间:
    2021
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Taghvaei, Amirhossein;Mehta, Prashant G.
  • 通讯作者:
    Mehta, Prashant G.
What is the Lagrangian for Nonlinear Filtering?
Diffusion Map-based Algorithm for Gain Function Approximation in the Feedback Particle Filter
反馈粒子滤波器中基于扩散图的增益函数逼近算法
An Optimal Transport Formulation of the Ensemble Kalman Filter
Minimum variance constrained estimator
最小方差约束估计器
  • DOI:
    10.1016/j.automatica.2021.110106
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    6.4
  • 作者:
    Mishra, Prabhat K.;Chowdhary, Girish;Mehta, Prashant G.
  • 通讯作者:
    Mehta, Prashant G.
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Prashant Mehta其他文献

Real World Data of Novel Talicabtagene Autoleucel (humanized CD19 CAR-T) from India; Ensuring Equitable Access with Excellent Safety and Efficacy Profile
  • DOI:
    10.1182/blood-2024-202335
  • 发表时间:
    2024-11-05
  • 期刊:
  • 影响因子:
  • 作者:
    Hasmukh Jain;Atharva Karulkar;Devanshi Kalra;Smrithi Ravikumar;Shreshtha Shah;Afrin Firfiray;Juber Pendhari;Manivasagam S;Anand Vaibhaw;Ashish Saroha;Ankesh K. Jaiswal;Alok Shetty;Lingaraj Nayak;Bhausaheb Bagal;Neeraj Siddharthan;Esha Kaul;Prashant Mehta;Anshul Gupta;Navin Khattry;Nishant Jindal
  • 通讯作者:
    Nishant Jindal
Diagnostic Nuances of Circulating CAR-T-Cell Evaluation Postinfusion – A Tertiary Care Oncology Center Experience From North India
  • DOI:
    10.1016/s2152-2650(24)01060-7
  • 发表时间:
    2024-09-01
  • 期刊:
  • 影响因子:
  • 作者:
    Nupur Das;Prashant Mehta;Pravas Mishra;Swati Pabbi;Rahul Katharia;Tanisha Singla;Saphalta Baghmar
  • 通讯作者:
    Saphalta Baghmar
Three-way Philadelphia Translocation [t(46, XX, t(9;22;16) (q34;q11.2;q24)] in Chronic Myeloid Leukemia: A Report of Two Cases with Review of the Literature.
慢性粒细胞白血病中的三向费城易位 [t(46, XX, t(9;22;16) (q34;q11.2;q24)]:两例报告及文献回顾。
  • DOI:
    10.4103/jcrt.jcrt_274_21
  • 发表时间:
    2024
  • 期刊:
  • 影响因子:
    1.3
  • 作者:
    M. Bhardwaj;S. K. Mishra;Aastha Gupta;Prashant Mehta;Shivani Sharma;S. Mohanty
  • 通讯作者:
    S. Mohanty
CD 19 CAR T-Cell Therapy in R/R B Cell Malignancies : A Real World Experience from CAR T Working Group, Delhi Ncr ,India
  • DOI:
    10.1182/blood-2024-205903
  • 发表时间:
    2024-11-05
  • 期刊:
  • 影响因子:
  • 作者:
    Prashant Mehta;Pravas Mishra;Dinesh Bhurani;Vidit Kapoor;Esha Kaul;Rayaz Ahmed;Saphalta Baghmar;Swati Pabbi;Rahul Katharia;Nupur Das;Narendra Agrawal;Rohan Halder;Roy Palatty;Reema Singh;Faran Naim;Jagsahib Kaur
  • 通讯作者:
    Jagsahib Kaur
The Impact of Website Design on Online Customer Buying Satisfaction and Loyalty to E-Tailers: An Exploratory Study of E-Tailers In India
网站设计对在线客户购买满意度和电子零售商忠诚度的影响:印度电子零售商的探索性研究
  • DOI:
    10.4018/irmj.287902
  • 发表时间:
    2022
  • 期刊:
  • 影响因子:
    0
  • 作者:
    Debarun Chakraborty;Jayanta Banerjee;Prashant Mehta;N. Singh
  • 通讯作者:
    N. Singh

Prashant Mehta的其他文献

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{{ truncateString('Prashant Mehta', 18)}}的其他基金

Distinguishing Between Human Activities in Real-Time Based on Wearable Sensor Data Using a Low-dimensional Model of Human Movement
使用人体运动的低维模型,基于可穿戴传感器数据实时区分人体活动
  • 批准号:
    1462773
  • 财政年份:
    2015
  • 资助金额:
    $ 37.8万
  • 项目类别:
    Standard Grant
I-Corps: Commercialization of Feedback Particle Filter for Target State Estimation
I-Corps:用于目标状态估计的反馈粒子滤波器的商业化
  • 批准号:
    1343554
  • 财政年份:
    2013
  • 资助金额:
    $ 37.8万
  • 项目类别:
    Standard Grant
Mean-field Oscillator Games with Application to Thalamocortical Network Dynamics
平均场振荡器游戏在丘脑皮质网络动力学中的应用
  • 批准号:
    1334987
  • 财政年份:
    2013
  • 资助金额:
    $ 37.8万
  • 项目类别:
    Standard Grant
CPS: Medium: Collaborative Research: GOALI: Methods for Network-Enabled Embedded Monitoring and Control for High-Performance Buildings
CPS:中:协作研究:GOALI:高性能建筑的网络嵌入式监控方法
  • 批准号:
    0931416
  • 财政年份:
    2010
  • 资助金额:
    $ 37.8万
  • 项目类别:
    Continuing Grant
Fundamental Limitations in Control of Nonlinear Systems with Application to Biology
非线性系统控制及其在生物学中的应用的基本限制
  • 批准号:
    0925534
  • 财政年份:
    2009
  • 资助金额:
    $ 37.8万
  • 项目类别:
    Continuing Grant
An Integrated Multi-Scale Stochastic Framework for Dynamic Analysis and Control of Transport Phenomena in Building Systems
用于建筑系统中传输现象动态分析和控制的集成多尺度随机框架
  • 批准号:
    0556352
  • 财政年份:
    2006
  • 资助金额:
    $ 37.8万
  • 项目类别:
    Standard Grant

相似海外基金

CAREER: Nonsmooth Control Systems for Societal Networks with Data-Assisted Feedback Loops: Theory and Algorithms
职业:具有数据辅助反馈环的社会网络的非平滑控制系统:理论和算法
  • 批准号:
    2305756
  • 财政年份:
    2022
  • 资助金额:
    $ 37.8万
  • 项目类别:
    Continuing Grant
An Innovative and Personalised Physiotherapy Exercise Technique Feedback Application Using Computer Vision Algorithms
使用计算机视觉算法的创新和个性化理疗运动技术反馈应用
  • 批准号:
    10045741
  • 财政年份:
    2022
  • 资助金额:
    $ 37.8万
  • 项目类别:
    Grant for R&D
CAREER: Nonsmooth Control Systems for Societal Networks with Data-Assisted Feedback Loops: Theory and Algorithms
职业:具有数据辅助反馈环的社会网络的非平滑控制系统:理论和算法
  • 批准号:
    2144076
  • 财政年份:
    2022
  • 资助金额:
    $ 37.8万
  • 项目类别:
    Continuing Grant
CRII: CPS: High-Performance Adaptive Hybrid Feedback Algorithms for Real-Time Optimization and Learning in Networked Transportation Systems
CRII:CPS:用于网络运输系统实时优化和学习的高性能自适应混合反馈算法
  • 批准号:
    1947613
  • 财政年份:
    2020
  • 资助金额:
    $ 37.8万
  • 项目类别:
    Standard Grant
CAREER: Synthesis of Feedback-based Online Algorithms for Power Grids
职业:基于反馈的电网在线算法综合
  • 批准号:
    1941896
  • 财政年份:
    2020
  • 资助金额:
    $ 37.8万
  • 项目类别:
    Continuing Grant
IUSE: EHR: Improving Undergraduate Algorithms Instructions with Online Feedback
IUSE:EHR:通过在线反馈改进本科生算法说明
  • 批准号:
    1903304
  • 财政年份:
    2019
  • 资助金额:
    $ 37.8万
  • 项目类别:
    Standard Grant
Scalable Symbolic Control: Computationally Efficient Design of Feedback Control Algorithms to Satisfy Complex Requirements
可扩展的符号控制:满足复杂要求的反馈控制算法的计算高效设计
  • 批准号:
    1906164
  • 财政年份:
    2019
  • 资助金额:
    $ 37.8万
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    Standard Grant
CRII: RI: Practical Algorithms for Robust Feedback Motion Planning Through Contact
CRII:RI:通过接触进行鲁棒反馈运动规划的实用算法
  • 批准号:
    1657186
  • 财政年份:
    2017
  • 资助金额:
    $ 37.8万
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    Standard Grant
Convergent Data-Based Algorithms for Model Reduction and Feedback Control of PDEs
用于偏微分方程模型简化和反馈控制的基于数据的收敛算法
  • 批准号:
    1217122
  • 财政年份:
    2012
  • 资助金额:
    $ 37.8万
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    Standard Grant
Studies on Feedback Path Identification and Adaptive Filter Algorithms Based on Information Quantity
基于信息量的反馈路径识别与自适应滤波算法研究
  • 批准号:
    19560381
  • 财政年份:
    2007
  • 资助金额:
    $ 37.8万
  • 项目类别:
    Grant-in-Aid for Scientific Research (C)
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