This paper presents a quantum-enhanced pulse-Doppler (PD) radar processing framework. It fuses quantum-correlated sensing with classical radar signal processing to improve target detection in complex electromagnetic conditions. We introduce coincidence counting and fidelity estimation, which enable target verification and false-alarm suppression under strong clutter and interference. Simulation experiments show higher detection probability under a low-false-alarm constraint. A two-stage “verification + recheck” mechanism remedies missed detections in the classical chain. The results indicate the potential of quantum radar techniques for practical seeker systems.
This paper presents a quantum-enhanced pulse-Doppler (PD) radar processing framework. It fuses quantum-correlated sensing with classical radar signal processing to improve target detection in complex electromagnetic conditions. We introduce coincidence counting and fidelity estimation, which enable target verification and false-alarm suppression under strong clutter and interference. Simulation experiments show higher detection probability under a low-false-alarm constraint. A two-stage “verification + recheck” mechanism remedies missed detections in the classical chain. The results indicate the potential of quantum radar techniques for practical seeker systems.
Quantum radar represents a major shift in sensing by leveraging quantum correlations and entanglement to detect targets beyond the line of sight in complex environments. Unlike classical radar, which suffers severe performance loss in dense urban areas due to multipath effects, clutter, and noise, quantum radar uses biphoton correlations to preserve strong detection sensitivity even under heavy interference. This chapter presents a comprehensive review of quantum radar systems, focusing on NLOS functionality. It describes key concepts such as biphoton generation through spontaneous parametric down-conversion, quantum illumination methods, and optimal detection strategies. Practical implementations using cryogenic superconducting nanowire single-photon detectors and AI-based signal processing are also discussed. The role of quantum radar in future 6G integrated sensing and communication frameworks is explored, highlighting uses in autonomous vehicle safety and smart city monitoring. Simulation studies show detection rates above 95% at a 1 km NLOS distance, with up to a tenfold SNR improvement over classical systems, while experiments demonstrate more than 20 dB of noise reduction. The chapter concludes by addressing ongoing challenges like decoherence, scalability, and standardization, and outlines a pathway toward deployable quantum radar technologies by 2030 for Industry 5.0 applications.
Quantum radar represents a major shift in sensing by leveraging quantum correlations and entanglement to detect targets beyond the line of sight in complex environments. Unlike classical radar, which suffers severe performance loss in dense urban areas due to multipath effects, clutter, and noise, quantum radar uses biphoton correlations to preserve strong detection sensitivity even under heavy interference. This chapter presents a comprehensive review of quantum radar systems, focusing on NLOS functionality. It describes key concepts such as biphoton generation through spontaneous parametric down-conversion, quantum illumination methods, and optimal detection strategies. Practical implementations using cryogenic superconducting nanowire single-photon detectors and AI-based signal processing are also discussed. The role of quantum radar in future 6G integrated sensing and communication frameworks is explored, highlighting uses in autonomous vehicle safety and smart city monitoring. Simulation studies show detection rates above 95% at a 1 km NLOS distance, with up to a tenfold SNR improvement over classical systems, while experiments demonstrate more than 20 dB of noise reduction. The chapter concludes by addressing ongoing challenges like decoherence, scalability, and standardization, and outlines a pathway toward deployable quantum radar technologies by 2030 for Industry 5.0 applications.
Quantum radar systems leverage entangled photon pairs to detect and identify targets in noisy or cluttered environments with sensitivity beyond classical limits. By transmitting one photon of an entangled pair toward a distant object while retaining its partner locally, the system exploits quantum correlations to improve signal discrimination, reduce noise susceptibility, and enhance detection probability. This paper outlines the physical principles, operational architecture, and performance advantages of entanglement‑based illumination, providing a clear foundation for future quantum‑enhanced sensing technologies.(If you want it shorter, longer, or more formal, tap: shorter paragraph, longer paragraph, more formal)
As new concept radar combing quantum technology with radar technology, quantum radar is an extension of traditional radar theory and has the potential to break through the limit of conventional radar detection performance. We study quantum radar optimum decision strategies for various signal and background forms and compare them with traditional photon‐counting strategies. Quantum optimum strategy gives better detection probability with fixed false‐alarm probability, thus reducing needed signal strength to detect the target, but its validity strongly depends on exact knowledge of signal forms. We briefly discuss the influence of deviating signal amplitudes and phases, and find that in the condition that the false‐alarm probability is very small quantum optimum strategy is still useful when the signal form varies in a small region.
For next-generation vehicle-to-everything (V2X) communications, there has been a growing emerging technology at the intersection of Radar and Communications, namely RadCom. RadCom provides many benefits such as efficient usage of bandwidth, joint detection and estimation, and improved tracking performance for future intelligent transportation. However, there is a limitation in the computation of parameters for large dimensions (antennas, users, or targets). To provide, a computational complexity advantage for the target detection and parameters, we introduce Quantum-assisted Radar Communication systems, namely QRADCOM. In this work, we have proposed algorithms for the multi-target detection hypothesis based on quantum phase estimation (QPE), and also the quantum inversion method for communication signal detection in presence of observation noise, interference and multi-tap wireless channel. We show numerical results and analysis as well for the QRADCOM framework on both classical and IBM-Quantum computers.
Integrated sensing and communication (ISAC) is emerging as a key enabler for spectrum-efficient and hardware-converged wireless networks. However, classical radar systems within ISAC architectures face fundamental limitations under low signal power and high-noise conditions. This paper proposes a novel framework that embeds quantum illumination radar into a base station to simultaneously support full-duplex classical communication and quantum-enhanced target detection. The resulting integrated quantum sensing and classical communication (IQSCC) system is optimized via a sum-rate maximization formulation subject to radar sensing constraints. The non-convex joint optimization of transmit power and beamforming vectors is tackled using the successive convex approximation technique. Furthermore, we derive performance bounds for classical and quantum radar protocols under the statistical detection theory, highlighting the quantum advantage in low signal-to-interference-plus-noise ratio regimes. Simulation results demonstrate that the proposed IQSCC system achieves a higher communication throughput than the conventional ISAC baseline while satisfying the sensing requirement.