Resolution Limits of Non-Adaptive 20 Questions Estimation for Tracking Multiple Moving Targets

2025-07-02

AI Summary

This paper investigates the resolution limit of the non-adaptive twenty questions framework for multi-mobile-target localization and tracking under query-dependent noisy channels, motivated by 5G MIMO beam tracking. It proposes a single-threshold decoding rule to significantly reduce computational complexity. A unified non-asymptotic and second-order asymptotic resolution bound is established, accommodating scenarios where both initial position and velocity are unknown. Key modeling innovations include threshold estimation based on mutual information density, piecewise-constant velocity assumptions, and explicit characterization of query-dependent channel noise. Theoretical analysis and numerical experiments demonstrate that the proposed method approaches the fundamental resolution limit in multi-transmitter beam tracking. This work establishes a new paradigm for low-overhead, high-accuracy, real-time mobile target tracking.

Technology Category

• Computer Vision: Motion & Tracking
• Search and Optimization: Mixed Discrete/Continuous Search
• Intelligent Robots: Localization, Mapping, and Navigation

Application Category

• Security and Privacy: Tracking, profiling, and countermeasures against them
• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments

Abstract

Motivated by the practical application of beam tracking of multiple devices in Multiple Input Multiple Output (MIMO) communication, we study the problem of non-adaptive twenty questions estimation for locating and tracking multiple moving targets under a query-dependent noisy channel. Specifically, we derive a non-asymptotic bound and a second-order asymptotic bound on resolution for optimal query procedures and provide numerical examples to illustrate our results. In particular, we demonstrate that the bound is achieved by a state estimator that thresholds the mutual information density over possible target locations. This single threshold decoding rule has reduced the computational complexity compared to the multiple threshold scheme proposed for locating multiple stationary targets (Zhou, Bai and Hero, TIT 2022). We discuss two special cases of our setting: the case with unknown initial location and known velocity, and the case with known initial location and unknown velocity. Both cases share the same theoretical benchmark {that applies to} stationary multiple target search in Zhou, Bai and Hero (TIT 2022) while the known initial location case is close to the theoretical benchmark for stationary target search when the maximal speed is inversely proportional to the number of queries. We also generalize our results to account for a piecewise constant velocity model introduced in Zhou and Hero (TIT 2023), where targets change velocity periodically. Finally, we illustrate our proposed algorithm for the application of beam tracking of multiple mobile transmitters in a 5G wireless network.

Problem

• Tracking multiple moving targets in MIMO communication
• Non-adaptive noisy channel estimation for target resolution
• Beam tracking for mobile transmitters in 5G networks

Innovation

• Non-adaptive query for tracking moving targets
• Single threshold decoding reduces complexity
• Generalizes to piecewise constant velocity model