全球定位系统2026，Vol.51Issue(3)：44-53,10.DOI:10.12265/j.gnss.2026017
基于注意力增强的三维速度约束手机GNSS/INS车载导航
Attention-enhanced three-dimensional velocity constraint for smartphone GNSS/INS vehicular navigation
摘要
Abstract
In urban canyons,tunnels,and other GNSS signal-blocked environments,the positioning performance of smartphones integrated with consumer-grade GNSS chipsets and inertial measurement unit(IMU)degrades dramatically.Although inertial navigation systems(INS)can continuously provide navigation solutions in GNSS-denied environments,the low-cost IMU embedded in smartphones suffer from rapid error divergence due to low accuracy and high noise.Traditional non-holonomic constraint(NHC)methods experience severe failure when zero-value assumptions are violated during vehicle maneuvers such as turning and U-turns,thereby affecting positioning accuracy.To address these issues,this paper proposes an attention-enhanced three-dimensional velocity constraint method for smartphone-based vehicular positioning.The method constructs a hybrid architecture integrating convolutional neural network(CNN),long short-term memory(LSTM)network,and attention mechanism.Taking raw six-axis IMU observations as input,it directly outputs three-dimensional vehicle velocity,functioning as a three-dimensional virtual odometer during GNSS outages to constrain IMU error accumulation.Specifically,CNN captures local IMU features for noise filtering,LSTM models temporal correlations,and the sliding window-based attention mechanism adaptively weights historical information according to current motion states.Experimental results demonstrate that the proposed method achieves a forward velocity prediction root mean square(RMS)error of 0.48 m/s,representing a 40%-55%reduction compared to existing methods.In GNSS-denied scenarios,the average horizontal positioning RMS is 7.2 m and vertical positioning RMS is 2.3 m,representing reductions of 98.3%and 97.0%respectively compared to the unconstrained scheme,and 79.8%and 39.5%respectively compared to the traditional NHC scheme,significantly improving smartphone positioning performance in GNSS-denied environments.关键词
手机车载导航/非完整性约束(NHC)/深度学习/注意力机制/三维速度约束/组合导航Key words
smartphone vehicular navigation/non-holonomic constraint(NHC)/deep learning/attention mechanism/three-dimensional velocity constraint/integrated navigation分类
天文与地球科学引用本文复制引用
冯译苇,耿江辉,栗广才,刘金成..基于注意力增强的三维速度约束手机GNSS/INS车载导航[J].全球定位系统,2026,51(3):44-53,10.基金项目
国家自然科学基金(42361134580,U25D8020,42204021) （42361134580,U25D8020,42204021）
精密大地测量与定位全国重点实验室自主部署项目(L25S640601) （L25S640601）
武汉市自然科学基金探索计划(2024040801020238) （2024040801020238）
陕西省重点研发计划(2025NC-YBXM-209) （2025NC-YBXM-209）
