Quantum Sensor Signal Processing
量子传感器信号处理
基本信息
- 批准号:RGPIN-2021-04182
- 负责人:
- 金额:$ 2.04万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2022
- 资助国家:加拿大
- 起止时间:2022-01-01 至 2023-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Sensors (specifically, radars/lidars/imagers) are of fundamental importance. In recent years, quantum information techniques have suggested that substantial gain in sensor performance is possible using quantum mechanical phenomena, such as the quantization of light and quantum entanglement. Most of the research to date has been done from a quantum information perspective. In addition, many of the proposed quantum radar designs are not practically feasible (for example, they may depend on desired advances in underpinning quantum technologies, such as quantum memories, or perhaps the precise detector structure is unknown). We propose to investigate quantum sensors that are practically realizable. Furthermore, we propose to carry out the research from a signal processing perspective, which would be essential for practical sensor development. This research will play an important role in guiding the development of quantum sensors. Signal processing theory and algorithms will be developed for these novel sensors. The research will guide the development of practical sensors in a wide variety of applications. In particular, the research will have shape the development of substantially improved sensing capability over the state-of-the-art in biomedical imaging, remote vital sign monitoring, and healthcare diagnostic applications. The proposal seeks to accomplish this via three objectives. The first objective is to develop signal processing models for practically realizable quantum sensors. The second objective is to develop quantum sensor performance prediction using statistical detection and estimation theory. Finally, in the third objective, experimental validation of the theoretical work will be completed by collaboration with quantum experimentalists. The impact of this research will be substantial. The theoretical work will enable a rigorous analysis of the practical quantum sensors. It will also shape the research on the quantum side by guiding researchers towards using quantum physics to improve key parameters for improved sensor performance. Use cases in public safety and biomedical engineering will provide suitable guidance for the research. HQPs will gain a deep understanding of sensor signal processing. In addition, they will develop the skills in mathematical modelling, principled approximations for real data analysis, and programming. This well-rounded education will ensure that the skills developed are highly transferable and applicable to many industrial sectors. It is expected that some HQP will go on to form companies developing next-generation quantum sensors for a variety of applications. I have extensive and proven experience in continuously developing advanced sensor signal processing algorithms based on rigorous mathematical modelling, refining them with real sensor data, and leading the real-world implementation effort. The proposed research program will accelerate the development of practical quantum sensors.
传感器(特别是雷达/激光雷达/成像仪)至关重要。近年来,量子信息技术已经表明,传感器性能的实质性增益是可能的,使用量子力学现象,如光的量子化和量子纠缠。迄今为止,大多数研究都是从量子信息的角度进行的。此外,许多提出的量子雷达设计实际上并不可行(例如,它们可能取决于支撑量子技术的预期进展,例如量子存储器,或者精确的检测器结构是未知的)。此外,我们建议从信号处理的角度进行研究,这将是必不可少的实际传感器的发展。该研究对量子传感器的发展具有重要的指导作用。信号处理理论和算法将开发这些新的传感器。该研究将指导各种应用中实用传感器的开发。特别是,该研究将在生物医学成像、远程生命体征监测和医疗诊断应用领域的最新技术水平上大幅提高传感能力。该提案试图通过三个目标来实现这一目标。第一个目标是为实际可实现的量子传感器开发信号处理模型。第二个目标是使用统计检测和估计理论开发量子传感器性能预测。最后,在第三个目标中,将与量子实验学家合作完成理论工作的实验验证。 这项研究的影响将是巨大的。理论工作将能够对实际的量子传感器进行严格的分析。它还将通过指导研究人员使用量子物理学来改善关键参数以提高传感器性能,从而塑造量子方面的研究。公共安全和生物医学工程中的用例将为研究提供适当的指导。HQP将深入了解传感器信号处理。此外,他们将开发数学建模,真实的数据分析和编程的原则近似的技能。这种全面的教育将确保所开发的技能具有高度的可转移性,并适用于许多工业部门。预计一些HQP将继续组建公司,为各种应用开发下一代量子传感器。我在基于严格的数学建模不断开发先进的传感器信号处理算法、使用真实的传感器数据对其进行改进以及领导实际实施工作方面拥有丰富的经验。拟议的研究计划将加速实用量子传感器的发展。
项目成果
期刊论文数量(0)
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会议论文数量(0)
专利数量(0)
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Balaji, Bhashyam其他文献
Convolutional Neural Networks for Classification of Drones Using Radars
- DOI:
10.3390/drones5040149 - 发表时间:
2021-12-01 - 期刊:
- 影响因子:4.8
- 作者:
Raval, Divy;Hunter, Emily;Balaji, Bhashyam - 通讯作者:
Balaji, Bhashyam
Target Detection Through Riemannian Geometric Approach With Application to Drone Detection
- DOI:
10.1109/access.2021.3105594 - 发表时间:
2021-01-01 - 期刊:
- 影响因子:3.9
- 作者:
Chahrour, Hossein;Dansereau, Richard M.;Balaji, Bhashyam - 通讯作者:
Balaji, Bhashyam
Performance Prediction for Coherent Noise Radars Using the Correlation Coefficient
- DOI:
10.1109/access.2021.3135292 - 发表时间:
2022-01-01 - 期刊:
- 影响因子:3.9
- 作者:
Luong, David;Balaji, Bhashyam;Rajan, Sreeraman - 通讯作者:
Rajan, Sreeraman
Airborne Maritime Surveillance Using Magnetic Anomaly Detection Signature
- DOI:
10.1109/taes.2020.2973866 - 发表时间:
2020-10-01 - 期刊:
- 影响因子:4.4
- 作者:
Sithiravel, Rajiv;Balaji, Bhashyam;Kirubarajan, Thiagalingam - 通讯作者:
Kirubarajan, Thiagalingam
Entanglement-Based Quantum Radar: From Myth to Reality
- DOI:
10.1109/maes.2020.2970261 - 发表时间:
2020-04-01 - 期刊:
- 影响因子:3.6
- 作者:
Luong, David;Rajan, Sreeraman;Balaji, Bhashyam - 通讯作者:
Balaji, Bhashyam
Balaji, Bhashyam的其他文献
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{{ truncateString('Balaji, Bhashyam', 18)}}的其他基金
Quantum Sensor Signal Processing
量子传感器信号处理
- 批准号:
RGPIN-2021-04182 - 财政年份:2021
- 资助金额:
$ 2.04万 - 项目类别:
Discovery Grants Program - Individual
Quantum Sensor Signal Processing
量子传感器信号处理
- 批准号:
DGECR-2021-00439 - 财政年份:2021
- 资助金额:
$ 2.04万 - 项目类别:
Discovery Launch Supplement
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