sTM32 ADC采集滤波算法，卡尔曼 中位值 同步对比输出源程序，芯片采用STM32f103c8t6.算法采用卡尔曼滤波算法中位值滤波算法，波形输出正常采集的卡尔曼 中位值三个波形输出，程序注释详
资源内容介绍
sTM32 ADC采集滤波算法，卡尔曼 中位值 同步对比输出源程序，芯片采用STM32f103c8t6.算法采用卡尔曼滤波算法中位值滤波算法，波形输出正常采集的卡尔曼 中位值三个波形输出，程序注释详细。 <link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/base.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/css/fancy.min.css" rel="stylesheet"/><link href="/image.php?url=https://csdnimg.cn/release/download_crawler_static/90240579/2/raw.css" rel="stylesheet"/><div id="sidebar" style="display: none"><div id="outline"></div></div><div class="pf w0 h0" data-page-no="1" id="pf1"><div class="pc pc1 w0 h0"><img alt="" class="bi x0 y0 w1 h1" src="/image.php?url=https://csdnimg.cn/release/download_crawler_static/90240579/bg1.jpg"/><div class="t m0 x1 h2 y1 ff1 fs0 fc0 sc0 ls0 ws0">文章标题<span class="ff2">：</span>基于<span class="_ _0"> </span><span class="ff3">STM32<span class="_ _1"> </span></span>的<span class="_ _0"> </span><span class="ff3">ADC<span class="_ _1"> </span></span>采集滤波算法研究及源程序实现</div><div class="t m0 x1 h2 y2 ff1 fs0 fc0 sc0 ls0 ws0">摘要<span class="ff2">：</span>本文以<span class="_ _0"> </span><span class="ff3">STM32f103c8t6<span class="_ _1"> </span></span>芯片为例<span class="ff2">，</span>通过引入卡尔曼滤波算法和中位值滤波算法<span class="ff2">，</span>实现了对</div><div class="t m0 x1 h2 y3 ff3 fs0 fc0 sc0 ls0 ws0">ADC<span class="_ _1"> </span><span class="ff1">采集数据的滤波处理<span class="ff2">，</span>并输出了滤波后的波形信号<span class="ff4">。</span>文章详细介绍了算法原理<span class="ff4">、</span>源程序实现以及</span></div><div class="t m0 x1 h2 y4 ff1 fs0 fc0 sc0 ls0 ws0">相应波形输出<span class="ff2">，</span>对关键代码进行了详细注释<span class="ff4">。</span></div><div class="t m0 x1 h2 y5 ff1 fs0 fc0 sc0 ls0 ws0">一<span class="ff4">、</span>引言</div><div class="t m0 x1 h2 y6 ff1 fs0 fc0 sc0 ls0 ws0">随着电子技术的不断发展<span class="ff2">，</span>嵌入式系统在各个领域得到了广泛应用<span class="ff2">，</span>而<span class="_ _0"> </span><span class="ff3">STM32<span class="_ _1"> </span></span>系列芯片作为一种功能</div><div class="t m0 x1 h2 y7 ff1 fs0 fc0 sc0 ls0 ws0">强大的嵌入式控制器<span class="ff2">，</span>其性能和稳定性备受推崇<span class="ff4">。</span>在嵌入式系统的开发过程中<span class="ff2">，</span>对于实时采集的模拟</div><div class="t m0 x1 h2 y8 ff1 fs0 fc0 sc0 ls0 ws0">信号<span class="ff2">，</span>滤波是一项非常重要的工作<span class="ff2">，</span>能够有效去除噪声干扰<span class="ff2">，</span>提高信号质量<span class="ff4">。</span>而卡尔曼滤波算法和中</div><div class="t m0 x1 h2 y9 ff1 fs0 fc0 sc0 ls0 ws0">位值滤波算法作为常用的滤波方法<span class="ff2">，</span>具有滤波效果好<span class="ff4">、</span>计算量小等优点<span class="ff2">，</span>因此在实际应用中被广泛采</div><div class="t m0 x1 h2 ya ff1 fs0 fc0 sc0 ls0 ws0">用<span class="ff4">。</span></div><div class="t m0 x1 h2 yb ff1 fs0 fc0 sc0 ls0 ws0">二<span class="ff4">、</span>算法原理</div><div class="t m0 x1 h2 yc ff3 fs0 fc0 sc0 ls0 ws0">2.1 <span class="ff1">卡尔曼滤波算法</span></div><div class="t m0 x1 h2 yd ff1 fs0 fc0 sc0 ls0 ws0">卡尔曼滤波算法是一种递推算法<span class="ff2">，</span>其根据当前的状态估计值和误差协方差<span class="ff2">，</span>结合测量得到的数据<span class="ff2">，</span>通</div><div class="t m0 x1 h2 ye ff1 fs0 fc0 sc0 ls0 ws0">过逐步的迭代更新<span class="ff2">，</span>实现对真实状态的估计<span class="ff4">。</span>具体来说<span class="ff2">，</span>卡尔曼滤波算法可以分为两个步骤<span class="ff2">：</span>预测和</div><div class="t m0 x1 h2 yf ff1 fs0 fc0 sc0 ls0 ws0">更新<span class="ff4">。</span>在预测步骤中<span class="ff2">，</span>通过上一时刻的状态估计值和误差协方差<span class="ff2">，</span>预测当前时刻的状态估计值和误差</div><div class="t m0 x1 h2 y10 ff1 fs0 fc0 sc0 ls0 ws0">协方差<span class="ff2">；</span>在更新步骤中<span class="ff2">，</span>通过当前时刻的测量值和预测值的比较<span class="ff2">，</span>更新状态估计值和误差协方差<span class="ff4">。</span>通</div><div class="t m0 x1 h2 y11 ff1 fs0 fc0 sc0 ls0 ws0">过连续的预测和更新<span class="ff2">，</span>可以逐渐减小估计值和真实值之间的误差<span class="ff2">，</span>实现滤波效果<span class="ff4">。</span></div><div class="t m0 x1 h2 y12 ff3 fs0 fc0 sc0 ls0 ws0">2.2 <span class="ff1">中位值滤波算法</span></div><div class="t m0 x1 h2 y13 ff1 fs0 fc0 sc0 ls0 ws0">中位值滤波算法是一种基于排序的滤波方法<span class="ff2">，</span>其主要思想是通过对采集的数据进行排序<span class="ff2">，</span>然后取中间</div><div class="t m0 x1 h2 y14 ff1 fs0 fc0 sc0 ls0 ws0">值作为滤波结果<span class="ff4">。</span>中位值滤波算法对于突变噪声具有很好的抑制作用<span class="ff2">，</span>能够有效去除异常值<span class="ff2">，</span>平滑信</div><div class="t m0 x1 h2 y15 ff1 fs0 fc0 sc0 ls0 ws0">号<span class="ff4">。</span>具体实现中<span class="ff2">，</span>将采集的数据存储在一个有序的缓冲区中<span class="ff2">，</span>然后取中间值作为滤波结果<span class="ff4">。</span>由于中位</div><div class="t m0 x1 h2 y16 ff1 fs0 fc0 sc0 ls0 ws0">值滤波算法的运算量较小<span class="ff2">，</span>适用于嵌入式系统等计算资源有限的应用场景<span class="ff4">。</span></div><div class="t m0 x1 h2 y17 ff1 fs0 fc0 sc0 ls0 ws0">三<span class="ff4">、</span>源程序实现</div><div class="t m0 x1 h2 y18 ff1 fs0 fc0 sc0 ls0 ws0">本文以<span class="_ _0"> </span><span class="ff3">STM32f103c8t6<span class="_ _1"> </span></span>芯片为例<span class="ff2">，</span>通过嵌入式<span class="_ _0"> </span><span class="ff3">C<span class="_ _1"> </span></span>语言编写了相应的源程序<span class="ff2">，</span>实现了对<span class="_ _0"> </span><span class="ff3">ADC<span class="_ _1"> </span></span>采集数</div><div class="t m0 x1 h2 y19 ff1 fs0 fc0 sc0 ls0 ws0">据的卡尔曼滤波和中位值滤波处理<span class="ff4">。</span>在程序中<span class="ff2">，</span>首先进行<span class="_ _0"> </span><span class="ff3">ADC<span class="_ _1"> </span></span>模块的初始化配置<span class="ff2">，</span>然后通过按照卡尔</div><div class="t m0 x1 h2 y1a ff1 fs0 fc0 sc0 ls0 ws0">曼滤波和中位值滤波的算法流程<span class="ff2">，</span>对采集的数据进行滤波处理<span class="ff4">。</span>最后<span class="ff2">，</span>通过串口输出滤波后的波形信</div><div class="t m0 x1 h2 y1b ff1 fs0 fc0 sc0 ls0 ws0">号<span class="ff2">，</span>以便进行观察和分析<span class="ff4">。</span>源程序中注释详细<span class="ff2">，</span>方便读者理解和参考<span class="ff4">。</span></div><div class="t m0 x1 h2 y1c ff1 fs0 fc0 sc0 ls0 ws0">四<span class="ff4">、</span>波形输出</div><div class="t m0 x1 h2 y1d ff1 fs0 fc0 sc0 ls0 ws0">通过实际运行测试<span class="ff2">，</span>本文实现了卡尔曼滤波和中位值滤波算法对<span class="_ _0"> </span><span class="ff3">ADC<span class="_ _1"> </span></span>采集数据的滤波处理<span class="ff2">，</span>并成功输</div><div class="t m0 x1 h2 y1e ff1 fs0 fc0 sc0 ls0 ws0">出了滤波后的波形信号<span class="ff4">。</span>通过波形输出的观察<span class="ff2">，</span>可以清晰看到滤波后的波形信号相较于原始采集数据</div></div><div class="pi" data-data='{"ctm":[1.568627,0.000000,0.000000,1.568627,0.000000,0.000000]}'></div></div>