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Bayes滤波器算法C++类说明文档,源码见Bayes滤波器算法

<a name="l00070"></a><a class="code" href="classBayesian__filter_1_1Unscented__scheme.html">00070</a> <span class="keyword">class </span><a class="code" href="classBayesian__filter_1_1Unscented__scheme.html">Unscented_scheme</a> : <span class="keyword">public</span> <a class="code" href="classBayesian__filter_1_1Linrz__kalman__filter.html">Linrz_kalman_filter</a>, <span class="keyword">public</span> <a class="code" href="classBayesian__filter_1_1Functional__filter.html">Functional_filter</a>
00071 {
00072 <span class="keyword">private</span>:
00073     size_t q_max;           <span class="comment">// Maxiumum size allocated for noise model, constructed before XX</span>
00074 <span class="keyword">public</span>:
<a name="l00075"></a><a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#o0">00075</a>     FM::ColMatrix <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#o0">XX</a>;       <span class="comment">// Unscented form of state, with associated kappa</span>
<a name="l00076"></a><a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#o1">00076</a>     <a class="code" href="classBayesian__filter_1_1Bayes__base.html#w0">Float</a> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#o1">kappa</a>;
00077 
00078     <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a0">Unscented_scheme</a> (size_t x_size, size_t z_initialsize = 0);
00079     <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html">Unscented_scheme</a>&amp; <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a1">operator= </a>(<span class="keyword">const</span> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html">Unscented_scheme</a>&amp;);
00080     <span class="comment">// Optimise copy assignment to only copy filter state</span>
00081 
00082     <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a2">init</a> ();
00083     <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a3">init_XX</a> ();
00084     <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a4">update</a> ();
00085     <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a5">update_XX</a> (Float kappa);
00086 
00087     <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a6">predict</a> (<a class="code" href="classBayesian__filter_1_1Unscented__predict__model.html">Unscented_predict_model</a>&amp; f);
00088     <span class="comment">// Efficient Unscented prediction </span>
00089     <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a6">predict</a> (<a class="code" href="classBayesian__filter_1_1Functional__predict__model.html">Functional_predict_model</a>&amp; f);
00090     <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a6">predict</a> (<a class="code" href="classBayesian__filter_1_1Addative__predict__model.html">Addative_predict_model</a>&amp; f);
<a name="l00091"></a><a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a9">00091</a>     <a class="code" href="classBayesian__filter_1_1Bayes__base.html#w0">Float</a> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a6">predict</a> (<a class="code" href="classBayesian__filter_1_1Linrz__predict__model.html">Linrz_predict_model</a>&amp; f)
00092     {   <span class="comment">// Adapt to use the more general addative model</span>
00093         <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a6">predict</a>(static_cast&lt;Addative_predict_model&amp;&gt;(f));
00094         <span class="keywordflow">return</span> 1.;      <span class="comment">// Always well condition for addative predict</span>
00095     }
00096     
00097     <a class="code" href="classBayesian__filter_1_1Bayes__base.html#w0">Float</a> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a10">observe</a> (Uncorrelated_addative_observe_model&amp; h, <span class="keyword">const</span> FM::Vec&amp; z);
00098     <a class="code" href="classBayesian__filter_1_1Bayes__base.html#w0">Float</a> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a10">observe</a> (Correlated_addative_observe_model&amp; h, <span class="keyword">const</span> FM::Vec&amp; z);
00099     <span class="comment">// Unscented filter implements general addative observe models </span>
00100     
<a name="l00101"></a><a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a12">00101</a>     <a class="code" href="classBayesian__filter_1_1Bayes__base.html#w0">Float</a> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a10">observe</a> (<a class="code" href="classBayesian__filter_1_1Linrz__uncorrelated__observe__model.html">Linrz_uncorrelated_observe_model</a>&amp; h, <span class="keyword">const</span> FM::Vec&amp; z)
00102     {   <span class="comment">// Adapt to use the more general addative model</span>
00103         <span class="keywordflow">return</span> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a10">observe</a> (static_cast&lt;Uncorrelated_addative_observe_model&amp;&gt;(h),z);
00104     }
<a name="l00105"></a><a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a13">00105</a>     <a class="code" href="classBayesian__filter_1_1Bayes__base.html#w0">Float</a> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a10">observe</a> (<a class="code" href="classBayesian__filter_1_1Linrz__correlated__observe__model.html">Linrz_correlated_observe_model</a>&amp; h, <span class="keyword">const</span> FM::Vec&amp; z)
00106     {   <span class="comment">// Adapt to use the more general addative model</span>
00107         <span class="keywordflow">return</span> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#a10">observe</a> (static_cast&lt;Correlated_addative_observe_model&amp;&gt;(h),z);
00108     }
00109 
00110 <span class="keyword">public</span>:                     <span class="comment">// Exposed Numerical Results</span>
<a name="l00111"></a><a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#o2">00111</a>     FM::Vec <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#o2">s</a>;                  <span class="comment">// Innovation</span>
<a name="l00112"></a><a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#o4">00112</a>     FM::SymMatrix <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#o3">S</a>, <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#o4">SI</a>;        <span class="comment">// Innovation Covariance and Inverse</span>
00113 
00114 <span class="keyword">protected</span>:
00115     <span class="keyword">virtual</span> <a class="code" href="classBayesian__filter_1_1Bayes__base.html#w0">Float</a> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#b0">predict_Kappa</a> (size_t size) <span class="keyword">const</span>;
00116     <span class="keyword">virtual</span> <a class="code" href="classBayesian__filter_1_1Bayes__base.html#w0">Float</a> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#b1">observe_Kappa</a> (size_t size) <span class="keyword">const</span>;
00117     <span class="comment">/* unscented Kappa values</span>
00118 <span class="comment">       default uses the rule which minimise mean squared error of 4th order term</span>
00119 <span class="comment">    */</span>
00120 
00121 <span class="keyword">protected</span>:                  <span class="comment">// allow fast operation if z_size remains constant</span>
<a name="l00122"></a><a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#p0">00122</a>     size_t <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#p0">last_z_size</a>;
00123     <span class="keywordtype">void</span> <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#b2">observe_size</a> (size_t z_size);
00124 
00125 <span class="keyword">private</span>:
00126     <span class="keywordtype">void</span> unscented (FM::ColMatrix&amp; XX, <span class="keyword">const</span> FM::Vec&amp; x, <span class="keyword">const</span> FM::SymMatrix&amp; X, Float scale);
00127     <span class="comment">/* Determine Unscented points for a distribution */</span>
00128     size_t x_size;
00129     size_t XX_size; <span class="comment">// 2*x_size+1</span>
00130 
00131 <span class="keyword">protected</span>:                  <span class="comment">// Permenantly allocated temps</span>
<a name="l00132"></a><a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#p1">00132</a>     FM::ColMatrix <a class="code" href="classBayesian__filter_1_1Unscented__scheme.html#p1">fXX</a>;
00133 };
00134 
00135 
00136 }<span class="comment">//namespace</span>
00137 <span class="preprocessor">#endif</span>
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