k60-keil

K60-Keil版本（下载安装MDK4.23）

/* ----------------------------------------------------------------------   
* Copyright (C) 2010 ARM Limited. All rights reserved.   
*   
* $Date:        15. July 2011  
* $Revision: 	V1.0.10  
*   
* Project: 	    CMSIS DSP Library   
* Title:	    arm_biquad_cascade_df1_32x64_q31.c   
*   
* Description:	High precision Q31 Biquad cascade filter processing function   
*   
* Target Processor: Cortex-M4/Cortex-M3/Cortex-M0
*  
* Version 1.0.10 2011/7/15 
*    Big Endian support added and Merged M0 and M3/M4 Source code.  
*   
* Version 1.0.3 2010/11/29  
*    Re-organized the CMSIS folders and updated documentation.   
*    
* Version 1.0.2 2010/11/11   
*    Documentation updated.    
*   
* Version 1.0.1 2010/10/05    
*    Production release and review comments incorporated.   
*   
* Version 1.0.0 2010/09/20    
*    Production release and review comments incorporated.   
*   
* Version 0.0.7  2010/06/10    
*    Misra-C changes done   
* -------------------------------------------------------------------- */

#include "arm_math.h"

/**   
 * @ingroup groupFilters   
 */

/**   
 * @defgroup BiquadCascadeDF1_32x64 High Precision Q31 Biquad Cascade Filter   
 *   
 * This function implements a high precision Biquad cascade filter which operates on   
 * Q31 data values.  The filter coefficients are in 1.31 format and the state variables   
 * are in 1.63 format.  The double precision state variables reduce quantization noise   
 * in the filter and provide a cleaner output.   
 * These filters are particularly useful when implementing filters in which the   
 * singularities are close to the unit circle.  This is common for low pass or high   
 * pass filters with very low cutoff frequencies.   
 *   
 * The function operates on blocks of input and output data   
 * and each call to the function processes <code>blockSize</code> samples through   
 * the filter. <code>pSrc</code> and <code>pDst</code> points to input and output arrays   
 * containing <code>blockSize</code> Q31 values.   
 *   
 * \par Algorithm   
 * Each Biquad stage implements a second order filter using the difference equation:   
 * <pre>   
 *     y[n] = b0 * x[n] + b1 * x[n-1] + b2 * x[n-2] + a1 * y[n-1] + a2 * y[n-2]   
 * </pre>   
 * A Direct Form I algorithm is used with 5 coefficients and 4 state variables per stage.   
 * \image html Biquad.gif "Single Biquad filter stage"   
 * Coefficients <code>b0, b1, and b2 </code> multiply the input signal <code>x[n]</code> and are referred to as the feedforward coefficients.   
 * Coefficients <code>a1</code> and <code>a2</code> multiply the output signal <code>y[n]</code> and are referred to as the feedback coefficients.   
 * Pay careful attention to the sign of the feedback coefficients.   
 * Some design tools use the difference equation   
 * <pre>   
 *     y[n] = b0 * x[n] + b1 * x[n-1] + b2 * x[n-2] - a1 * y[n-1] - a2 * y[n-2]   
 * </pre>   
 * In this case the feedback coefficients <code>a1</code> and <code>a2</code> must be negated when used with the CMSIS DSP Library.   
 *   
 * \par   
 * Higher order filters are realized as a cascade of second order sections.   
 * <code>numStages</code> refers to the number of second order stages used.   
 * For example, an 8th order filter would be realized with <code>numStages=4</code> second order stages.   
 * \image html BiquadCascade.gif "8th order filter using a cascade of Biquad stages"   
 * A 9th order filter would be realized with <code>numStages=5</code> second order stages with the coefficients for one of the stages configured as a first order filter (<code>b2=0</code> and <code>a2=0</code>).   
 *   
 * \par   
 * The <code>pState</code> points to state variables array .   
 * Each Biquad stage has 4 state variables <code>x[n-1], x[n-2], y[n-1],</code> and <code>y[n-2]</code> and each state variable in 1.63 format to improve precision.   
 * The state variables are arranged in the array as:   
 * <pre>   
 *     {x[n-1], x[n-2], y[n-1], y[n-2]}   
 * </pre>   
 *   
 * \par   
 * The 4 state variables for stage 1 are first, then the 4 state variables for stage 2, and so on.   
 * The state array has a total length of <code>4*numStages</code> values of data in 1.63 format.   
 * The state variables are updated after each block of data is processed; the coefficients are untouched.   
 *   
 * \par Instance Structure   
 * The coefficients and state variables for a filter are stored together in an instance data structure.   
 * A separate instance structure must be defined for each filter.   
 * Coefficient arrays may be shared among several instances while state variable arrays cannot be shared.   
 *   
 * \par Init Function   
 * There is also an associated initialization function which performs the following operations:   
 * - Sets the values of the internal structure fields.   
 * - Zeros out the values in the state buffer.   
 * \par   
 * Use of the initialization function is optional.   
 * However, if the initialization function is used, then the instance structure cannot be placed into a const data section.   
 * To place an instance structure into a const data section, the instance structure must be manually initialized.   
 * Set the values in the state buffer to zeros before static initialization.   
 * For example, to statically initialize the filter instance structure use   
 * <pre>   
 *     arm_biquad_cas_df1_32x64_ins_q31 S1 = {numStages, pState, pCoeffs, postShift};   
 * </pre>   
 * where <code>numStages</code> is the number of Biquad stages in the filter; <code>pState</code> is the address of the state buffer;   
 * <code>pCoeffs</code> is the address of the coefficient buffer; <code>postShift</code> shift to be applied which is described in detail below.   
 * \par Fixed-Point Behavior   
 * Care must be taken while using Biquad Cascade 32x64 filter function.   
 * Following issues must be considered:   
 * - Scaling of coefficients   
 * - Filter gain   
 * - Overflow and saturation   
 *   
 * \par   
 * Filter coefficients are represented as fractional values and   
 * restricted to lie in the range <code>[-1 +1)</code>.   
 * The processing function has an additional scaling parameter <code>postShift</code>   
 * which allows the filter coefficients to exceed the range <code>[+1 -1)</code>.   
 * At the output of the filter's accumulator is a shift register which shifts the result by <code>postShift</code> bits.   
 * \image html BiquadPostshift.gif "Fixed-point Biquad with shift by postShift bits after accumulator"   
 * This essentially scales the filter coefficients by <code>2^postShift</code>.   
 * For example, to realize the coefficients   
 * <pre>   
 *    {1.5, -0.8, 1.2, 1.6, -0.9}   
 * </pre>   
 * set the Coefficient array to:   
 * <pre>   
 *    {0.75, -0.4, 0.6, 0.8, -0.45}   
 * </pre>   
 * and set <code>postShift=1</code>   
 *   
 * \par   
 * The second thing to keep in mind is the gain through the filter.   
 * The frequency response of a Biquad filter is a function of its coefficients.   
 * It is possible for the gain through the filter to exceed 1.0 meaning that the filter increases the amplitude of certain frequencies.   
 * This means that an input signal with amplitude < 1.0 may result in an output > 1.0 and these are saturated or overflowed based on the implementation of the filter.   
 * To avoid this behavior the filter needs to be scaled down such that its peak gain < 1.0 or the input signal must be scaled down so that the combination of input and filter are never overflowed.   
 *   
 * \par   
 * The third item to consider is the overflow and saturation behavior of the fixed-point Q31 version.   
 * This is described in the function specific documentation below.   
 */

/**   
 * @addtogroup BiquadCascadeDF1_32x64   
 * @{   
 */

/**   
 * @details   
   
 * @param[in]  *S points to an instance of the high precision Q31 Biquad cascade filter.   
 * @param[in]  *pSrc points to the block of input data.   
 * @param[out] *pDst points to the block of output data.   
 * @param[in]  blockSize number of samples to process.   
 * @return none.   
 *   
 * \par   
 * The function is implemented using an internal 64-bit accumulator.   
 * The accumulator has a 2.62 format and maintains full precision of the intermediate multiplication results but provides only a single guard bit.   
 * Thus, if the accumulator result overflows it wraps around rather than clip.   
 * In order to avoid overflows completely the input signal must be scaled down by 2 bits and lie in the range [-0.25 +0.25).   
 * After all 5 multiply-accumulates are performed, the 2.62 accumulator is shifted by <code>postShift</code> bits and the result truncated to   
 * 1.31 format by discarding the low 32 bits.   
 *   
 * \par   
 * Two related functions are provided in the CMSIS DSP library.   
 * <code>arm_biquad_cascade_df1_q31()</code> implements a Biquad cascade with 32-bit coefficients and state variables with a Q63 accumulator.   
 * <code>arm_biquad_cascade_df1_fast_q31()</code> implements a Biquad cascade with 32-bit coefficients and state variables with a Q31 accumulator.   
 */

void arm_biquad_cas_df1_32x64_q31(
  const arm_biquad_cas_df1_32x64_ins_q31 * S,
  q31_t * pSrc,
  q31_t * pDst,
  uint32_t blockSize)
{
  q31_t *pIn = pSrc;                             /*  input pointer initialization  */
  q31_t *pOut = pDst;                            /*  output pointer initialization */
  q63_t *pState = S->pState;                     /*  state pointer initialization  */
  q31_t *pCoeffs = S->pCoeffs;                   /*  coeff pointer initialization  */
  q63_t acc;                                     /*  accumulator                   */
  q63_t Xn1, Xn2, Yn1, Yn2;                      /*  Filter state variables        */
  q31_t b0, b1, b2, a1, a2;                      /*  Filter coefficients           */
  q63_t Xn;                                      /*  temporary input               */
  int32_t shift = (int32_t) S->postShift + 1;    /*  Shift to be applied to the output */
  uint32_t sample, stage = S->numStages;         /*  loop counters                     */


#ifndef ARM_MATH_CM0

  /* Run the below code for Cortex-M4 and Cortex-M3 */

  do
  {
    /* Reading the coefficients */
    b0 = *pCoeffs++;
    b1 = *pCoeffs++;
    b2 = *pCoeffs++;
    a1 = *pCoeffs++;
    a2 = *pCoeffs++;

    /* Reading the state values */
    Xn1 = pState[0];
    Xn2 = pState[1];
    Yn1 = pState[2];
    Yn2 = pState[3];

    /* Apply loop unrolling and compute 4 output values simultaneously. */
    /* The variable acc hold output value that is being computed and   
     * stored in the destination buffer   
     * acc =  b0 * x[n] + b1 * x[n-1] + b2 * x[n-2] + a1 * y[n-1] + a2 * y[n-2]   
     */

    sample = blockSize >> 2u;

    /* First part of the processing with loop unrolling. Compute 4 outputs at a time.   
     ** a second loop below computes the remaining 1 to 3 samples. */
    while(sample > 0u)
    {
      /* Read the input */
      Xn = *pIn++;

      /* The value is shifted to the MSB to perform 32x64 multiplication */
      Xn = Xn << 32;

      /* acc =  b0 * x[n] + b1 * x[n-1] + b2 * x[n-2] + a1 * y[n-1] + a2 * y[n-2] */

      /* acc =  b0 * x[n] */
      acc = mult32x64(Xn, b0);
      /* acc +=  b1 * x[n-1] */
      acc += mult32x64(Xn1, b1);
      /* acc +=  b[2] * x[n-2] */
      acc += mult32x64(Xn2, b2);
      /* acc +=  a1 * y[n-1] */