基于数据融合的MEMS阵列加速度传感器实现方法

针对单MEMS加速度计性能有限无法满足实际工程中日益复杂且严苛的检测需求的问题，提出了一种基于数据融合的MEMS阵列加速度传感器实现方法。首先，设计了MEMS阵列加速度传感器的系统架构，并分析了对数据融合算法的技术需求；然后，针对已有的数据融合技术无法满足MEMS阵列加速度传感器的精度与实时性要求的问题，提出了基于离散对数映射的自整定加权融合算法，在此基础上，设计了MEMS阵列加速度传感器的仿真验证方案。仿真实验结果表明，提出的方法通过三个不同范围MEMS加速度计的阵列集成提高了信号检测能力，相比于最优拼接法其平均损失降低了6.1%，且融合数据精度优于各个加速度传感器的原始仿真数据，是高性能MEMS阵列加速度传感器的有效实现方案。

Method of Realizing MEMS Array Acceleration Sensor Based on Data Fusion

Aiming the problem that the limited performance of a single MEMS accelerometer cannot meet the increasingly complex and stringent detection requirements in practical engineering, a method of realizing MEMS array acceleration sensors based on data fusion is proposed in this paper. First, the system architecture of the MEMS array acceleration sensor is designed, and the technical specifications for the data fusion algorithm are analyzed. Then, we propose a self-tuning weighted fusion algorithm based on discrete logarithmic mapping to solve the problem that the existing data fusion technology cannot meet the accuracy and real-time needs of the MEMS array acceleration sensor. On this basis, the simulation verification scheme of the MEMS array acceleration sensor is designed. Results of the simulation experiment show that the proposed method improves the signal detection capability through the array integration of three MEMS accelerometers with different ranges, its average loss is reduced by 6.1% compared with the optimal splicing method, and the accuracy of the fused data is better than the original simulation data of each accelerometer, which is an effective implementation scheme for high-performance MEMS array acceleration sensors.