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首页> 外文期刊>IEEE Transactions on Industrial Electronics >Processing performance of two Kalman filter algorithms with a DSP32C by using assembly and C languages
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Processing performance of two Kalman filter algorithms with a DSP32C by using assembly and C languages

机译:使用汇编语言和C语言使用DSP32C处理两种卡尔曼滤波器算法的性能

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摘要

Two Kalman filter algorithms are implemented with a DSP32C processor. These two Kalman filters use conventional matrix operation and U-D factorization algorithms, respectively. The real-time processing performance of each algorithm is evaluated in terms of throughput, program and data memory sizes. Both DSP32C assembly and high-level C language programs of these two algorithms are developed (a total of four programs) for evaluating the coding efficiency. It is observed that both algorithms can be more efficiently programmed by using assembly language, a matrix-based algorithm enjoys its simple and regular operations so that less program memory is required in both assembly and in C languages, the U-D factorization algorithm involves fewer multiply-accumulate operations and provides a fast throughput in C language only, and the advantage of less multiply-accumulate operations in U-D factorization algorithm no longer exists in assembly language when the number of states of a Kalman filter is large.
机译:DSP32C处理器实现了两种卡尔曼滤波器算法。这两个卡尔曼滤波器分别使用常规矩阵运算和U-D分解算法。根据吞吐量,程序和数据存储器大小评估每种算法的实时处理性能。开发这两种算法的DSP32C汇编程序和高级C语言程序(总共四个程序)来评估编码效率。可以看出,使用汇编语言可以对两种算法进行更有效的编程,基于矩阵的算法具有简单且常规的操作,因此汇编语言和C语言都需要较少的程序存储空间,UD分解算法所涉及的乘法运算较少。累加运算仅在C语言中提供快速的吞吐量,而当Kalman滤波器的状态数很大时,汇编语言中不再存在UD分解算法中较少乘法累加运算的优点。

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