CAJ | 학술논문

针对惯性传感器信号处理的特点，提出了基于稀疏表示的信号滤波处理系统模型和方法。通过 K-SVD算法对信号学习训练获得字典，为了减少计算量，满足实时性，尽量降低字典的大小，仿真结果表明，在满足一定精度的条件下，字典的大小最小为3×10。在该字典下对信号进行稀疏表示和重构，改变信号的输入方式，可以实现信号的实时滤波。仿真结果表明提出的滤波方法能有效地消除噪声，改善输出信号精度，可以提高信噪比最大为4．5 dB。该滤波方法与传统的滤波方法相比有较大的优势，为惯性传感器信号处理提供了一种新的方法。
침대관성전감기신호처리적특점，제출료기우희소표시적신호려파처리계통모형화방법。통과 K-SVD산법대신호학습훈련획득자전，위료감소계산량，만족실시성，진량강저자전적대소，방진결과표명，재만족일정정도적조건하，자전적대소최소위3×10。재해자전하대신호진행희소표시화중구，개변신호적수입방식，가이실현신호적실시려파。방진결과표명제출적려파방법능유효지소제조성，개선수출신호정도，가이제고신조비최대위4．5 dB。해려파방법여전통적려파방법상비유교대적우세，위관성전감기신호처리제공료일충신적방법。
According to the characteristics of inertial sensor signal processing, this paper proposed the signal processing sys-tem and method based on sparse representation.Through the K-SVD algorithm of signal learning training to obtain the dictiona-ry, and in order to reduce the amount of computation to meet the real-time, as far as possible to reduce the size of the dictiona-ry, the simulation results show that, under certain precision condition, the minimum size of the dictionary is 3 ×10.Then, in the dictionary under the sparse representation and reconstruction of signals, while changing the input signal, it could achieve signal real-time filtering.The simulation results show that the proposed method can effectively eliminate the noise, improve the accuracy of output signals, and improve SNR up to 4.5 dB.The filtering method has more advantages than the traditional method, and provides a new method for inertial sensor signal processing.