Enhancement of Target Localization Based on Angle-of-Arrival Measurement via Quantum Sensor Networks
Quantum sensing and precision measurement technology based on non-classical characteristics such as compression and entanglement provide a novel way to improve the accuracy of parameter estimation. This paper proposes a quantum-enhanced angle-of-arrival (AoA) estimation method to address the problem of decreased localization accuracy due to the low angle measurement accuracy in traditional direction-finding cross-localization models.
The localization performance of distributed quantum sensor networks is analyzed based on this scheme. Taking edge sensors as reference nodes, the phase of signals and their higher-order derivatives can be estimated through multiple linearly arranged sensor networks.
By optimally adjusting the weight ratio of each sensor node to configure the sensor network, its sensing measurement accuracy can be significantly improved when compared to existing schemes. The spatial positioning accuracy is provided, which verifies the superiority of the direction-finding cross-positioning model based on quantum-enhanced sensor networks.
In this paper, the parameter estimation in quantum target detection and localization is extended to quantum sensor networks with multiple nodes. In the context of quantum sensor network structure design, previous quantum sensor positioning studies often use separate sensor combination positioning schemes, where a single sensor is used to enhance and measure a specific positioning parameter, and then combined and solved to obtain positioning results.
With the development of distributed quantum sensing theory and technology, multi-component entanglement can be used to improve the performance of global parameter estimation of sensor networks. It preserves valuable quantum entanglement resources and significantly expands the application of quantum sensing measurements in various fields, including phased array radar, satellite navigation and positioning and remote sensing detection imaging.
Based on the theory of distributed quantum sensing measurement, a distributed sensor network localization scheme with quantum-enhanced AoA estimation is proposed. Its detection and localization performance gain are also studied in detail.
Firstly, the quantum sensor network model based on direction finding cross-positioning is introduced, and the finite difference method for AoA estimation in quantum sensor networks is presented. Then, the theoretical accuracy of phase shift parameter estimation in quantum sensor networks is deduced.
The work demonstrates the gain of squeezed state-based separated entanglement and distributed entanglement schemes on AoA parameter estimation performance, highlighting the potential advantages of distributed quantum sensor networks in parameter estimation applications.
Taking the four-component entangled network as an example, the distributed quantum sensor network is used to estimate the AoA of radio frequency signals. The study shows that, taking the edge sensor as the reference node, the AoA estimation of any linearly arranged sensor can be achieved through phase observation. The higher derivative and the accuracy are significantly better than those of only the first derivative.
Quantum sensing networks based on AoA measurements have many applications, such as target detection, positioning, and tracking. With further advancements in schemes and designs, the localization of quantum sensing networks based on AoA measurements is expected to improve significantly.