range-dopplerHeatmap_AWR1642.py

import serial
import time
import numpy as np
import matplotlib.pyplot as plt

# TO DO: Add your own config file
configFileName = '1642RangeDoppler.cfg'
CLIport = {}
Dataport = {}
byteBuffer = np.zeros(2**15,dtype = 'uint8')
byteBufferLength = 0


# ------------------------------------------------------------------

# Function to configure the serial ports and send the data from
# the configuration file to the radar
def serialConfig(configFileName):
    
    global CLIport
    global Dataport
    # Open the serial ports for the configuration and the data ports
    
    # Raspberry pi
    CLIport = serial.Serial('/dev/ttyACM0', 115200)
    Dataport = serial.Serial('/dev/ttyACM1', 921600)
    
    # Windows
    #CLIport = serial.Serial('COM3', 115200)
    #Dataport = serial.Serial('COM4', 921600)

    # Read the configuration file and send it to the board
    config = [line.rstrip('\r\n') for line in open(configFileName)]
    for i in config:
        CLIport.write((i+'\n').encode())
        print(i)
        time.sleep(0.01)
        
    return CLIport, Dataport

# ------------------------------------------------------------------

# Function to parse the data inside the configuration file
def parseConfigFile(configFileName):
    configParameters = {} # Initialize an empty dictionary to store the configuration parameters
    
    # Read the configuration file and send it to the board
    config = [line.rstrip('\r\n') for line in open(configFileName)]
    for i in config:
        
        # Split the line
        splitWords = i.split(" ")
        
        # Hard code the number of antennas, change if other configuration is used
        numRxAnt = 4
        numTxAnt = 2
        
        # Get the information about the profile configuration
        if "profileCfg" in splitWords[0]:
            startFreq = int(float(splitWords[2]))
            idleTime = int(splitWords[3])
            rampEndTime = float(splitWords[5])
            freqSlopeConst = float(splitWords[8])
            numAdcSamples = int(splitWords[10])
            numAdcSamplesRoundTo2 = 1
            
            while numAdcSamples > numAdcSamplesRoundTo2:
                numAdcSamplesRoundTo2 = numAdcSamplesRoundTo2 * 2
                
            digOutSampleRate = int(splitWords[11])
            
        # Get the information about the frame configuration    
        elif "frameCfg" in splitWords[0]:
            
            chirpStartIdx = int(splitWords[1])
            chirpEndIdx = int(splitWords[2])
            numLoops = int(splitWords[3])
            numFrames = int(splitWords[4])
            framePeriodicity = int(splitWords[5])

            
    # Combine the read data to obtain the configuration parameters           
    numChirpsPerFrame = (chirpEndIdx - chirpStartIdx + 1) * numLoops
    configParameters["numDopplerBins"] = numChirpsPerFrame / numTxAnt
    configParameters["numRangeBins"] = numAdcSamplesRoundTo2
    configParameters["rangeResolutionMeters"] = (3e8 * digOutSampleRate * 1e3) / (2 * freqSlopeConst * 1e12 * numAdcSamples)
    configParameters["rangeIdxToMeters"] = (3e8 * digOutSampleRate * 1e3) / (2 * freqSlopeConst * 1e12 * configParameters["numRangeBins"])
    configParameters["dopplerResolutionMps"] = 3e8 / (2 * startFreq * 1e9 * (idleTime + rampEndTime) * 1e-6 * configParameters["numDopplerBins"] * numTxAnt)
    configParameters["maxRange"] = (300 * 0.9 * digOutSampleRate)/(2 * freqSlopeConst * 1e3)
    configParameters["maxVelocity"] = 3e8 / (4 * startFreq * 1e9 * (idleTime + rampEndTime) * 1e-6 * numTxAnt)
    
    return configParameters
   
# ------------------------------------------------------------------

# Funtion to read and parse the incoming data
def readAndParseData16xx(Dataport, configParameters):
    global byteBuffer, byteBufferLength

    # Constants
    OBJ_STRUCT_SIZE_BYTES = 12
    BYTE_VEC_ACC_MAX_SIZE = 2**15
    MMWDEMO_UART_MSG_DETECTED_POINTS = 1
    MMWDEMO_UART_MSG_RANGE_PROFILE   = 2
    MMWDEMO_OUTPUT_MSG_NOISE_PROFILE = 3
    MMWDEMO_OUTPUT_MSG_AZIMUT_STATIC_HEAT_MAP = 4
    MMWDEMO_OUTPUT_MSG_RANGE_DOPPLER_HEAT_MAP = 5
    maxBufferSize = 2**15
    magicWord = [2, 1, 4, 3, 6, 5, 8, 7]
    
    # Initialize variables
    magicOK = 0 # Checks if magic number has been read
    dataOK = 0 # Checks if the data has been read correctly
    frameNumber = 0
    detObj = {}
    tlv_type = 0
    
    readBuffer = Dataport.read(Dataport.in_waiting)
    byteVec = np.frombuffer(readBuffer, dtype = 'uint8')
    byteCount = len(byteVec)
    
    # Check that the buffer is not full, and then add the data to the buffer
    if (byteBufferLength + byteCount) < maxBufferSize:
        byteBuffer[byteBufferLength:byteBufferLength + byteCount] = byteVec[:byteCount]
        byteBufferLength = byteBufferLength + byteCount
        
    # Check that the buffer has some data
    if byteBufferLength > 16:
        
        # Check for all possible locations of the magic word
        possibleLocs = np.where(byteBuffer == magicWord[0])[0]

        # Confirm that is the beginning of the magic word and store the index in startIdx
        startIdx = []
        for loc in possibleLocs:
            check = byteBuffer[loc:loc+8]
            if np.all(check == magicWord):
                startIdx.append(loc)
               
        # Check that startIdx is not empty
        if startIdx:
            
            # Remove the data before the first start index
            if startIdx[0] > 0 and startIdx[0] < byteBufferLength:
                byteBuffer[:byteBufferLength-startIdx[0]] = byteBuffer[startIdx[0]:byteBufferLength]
                byteBuffer[byteBufferLength-startIdx[0]:] = np.zeros(len(byteBuffer[byteBufferLength-startIdx[0]:]),dtype = 'uint8')
                byteBufferLength = byteBufferLength - startIdx[0]
                
            # Check that there have no errors with the byte buffer length
            if byteBufferLength < 0:
                byteBufferLength = 0
                
            # word array to convert 4 bytes to a 32 bit number
            word = [1, 2**8, 2**16, 2**24]
            
            # Read the total packet length
            totalPacketLen = np.matmul(byteBuffer[12:12+4],word)
            
            # Check that all the packet has been read
            if (byteBufferLength >= totalPacketLen) and (byteBufferLength != 0):
                magicOK = 1
    
    # If magicOK is equal to 1 then process the message
    if magicOK:
        # word array to convert 4 bytes to a 32 bit number
        word = [1, 2**8, 2**16, 2**24]
        
        # Initialize the pointer index
        idX = 0
        
        # Read the header
        magicNumber = byteBuffer[idX:idX+8]
        idX += 8
        version = format(np.matmul(byteBuffer[idX:idX+4],word),'x')
        idX += 4
        totalPacketLen = np.matmul(byteBuffer[idX:idX+4],word)
        idX += 4
        platform = format(np.matmul(byteBuffer[idX:idX+4],word),'x')
        idX += 4
        frameNumber = np.matmul(byteBuffer[idX:idX+4],word)
        idX += 4
        timeCpuCycles = np.matmul(byteBuffer[idX:idX+4],word)
        idX += 4
        numDetectedObj = np.matmul(byteBuffer[idX:idX+4],word)
        idX += 4
        numTLVs = np.matmul(byteBuffer[idX:idX+4],word)
        idX += 4
        subFrameNumber = np.matmul(byteBuffer[idX:idX+4],word)
        idX += 4
        
        # Read the TLV messages
        for tlvIdx in range(numTLVs):
            
            # word array to convert 4 bytes to a 32 bit number
            word = [1, 2**8, 2**16, 2**24]

            # Check the header of the TLV message
            try:
                tlv_type = np.matmul(byteBuffer[idX:idX+4],word)
                idX += 4
                tlv_length = np.matmul(byteBuffer[idX:idX+4],word)
                idX += 4
            except:
                pass
            
            # Read the data depending on the TLV message
            if tlv_type == MMWDEMO_UART_MSG_DETECTED_POINTS:
                            
                # word array to convert 4 bytes to a 16 bit number
                word = [1, 2**8]
                tlv_numObj = np.matmul(byteBuffer[idX:idX+2],word)
                idX += 2
                tlv_xyzQFormat = 2**np.matmul(byteBuffer[idX:idX+2],word)
                idX += 2
                
                # Initialize the arrays
                rangeIdx = np.zeros(tlv_numObj,dtype = 'int16')
                dopplerIdx = np.zeros(tlv_numObj,dtype = 'int16')
                peakVal = np.zeros(tlv_numObj,dtype = 'int16')
                x = np.zeros(tlv_numObj,dtype = 'int16')
                y = np.zeros(tlv_numObj,dtype = 'int16')
                z = np.zeros(tlv_numObj,dtype = 'int16')
                
                for objectNum in range(tlv_numObj):
                    
                    # Read the data for each object
                    rangeIdx[objectNum] =  np.matmul(byteBuffer[idX:idX+2],word)
                    idX += 2
                    dopplerIdx[objectNum] = np.matmul(byteBuffer[idX:idX+2],word)
                    idX += 2
                    peakVal[objectNum] = np.matmul(byteBuffer[idX:idX+2],word)
                    idX += 2
                    x[objectNum] = np.matmul(byteBuffer[idX:idX+2],word)
                    idX += 2
                    y[objectNum] = np.matmul(byteBuffer[idX:idX+2],word)
                    idX += 2
                    z[objectNum] = np.matmul(byteBuffer[idX:idX+2],word)
                    idX += 2
                    
                # Make the necessary corrections and calculate the rest of the data
                rangeVal = rangeIdx * configParameters["rangeIdxToMeters"]
                dopplerIdx[dopplerIdx > (configParameters["numDopplerBins"]/2 - 1)] = dopplerIdx[dopplerIdx > (configParameters["numDopplerBins"]/2 - 1)] - 65535
                dopplerVal = dopplerIdx * configParameters["dopplerResolutionMps"]
                #x[x > 32767] = x[x > 32767] - 65536
                #y[y > 32767] = y[y > 32767] - 65536
                #z[z > 32767] = z[z > 32767] - 65536
                x = x / tlv_xyzQFormat
                y = y / tlv_xyzQFormat
                z = z / tlv_xyzQFormat
                
                # Store the data in the detObj dictionary
                detObj = {"numObj": tlv_numObj, "rangeIdx": rangeIdx, "range": rangeVal, "dopplerIdx": dopplerIdx, \
                          "doppler": dopplerVal, "peakVal": peakVal, "x": x, "y": y, "z": z}
                
                dataOK = 1

            elif tlv_type == MMWDEMO_OUTPUT_MSG_RANGE_DOPPLER_HEAT_MAP:

                # Get the number of bytes to read
                numBytes = 2*configParameters["numRangeBins"]*configParameters["numDopplerBins"]

                # Convert the raw data to int16 array
                payload = byteBuffer[idX:idX + numBytes]
                idX += numBytes
                rangeDoppler = payload.view(dtype=np.int16)

                # Some frames have strange values, skip those frames
                # TO DO: Find why those strange frames happen
                if np.max(rangeDoppler) > 10000:
                    continue

                # Convert the range doppler array to a matrix
                rangeDoppler = np.reshape(rangeDoppler, (configParameters["numDopplerBins"], configParameters["numRangeBins"]),'F') #Fortran-like reshape
                rangeDoppler = np.append(rangeDoppler[int(len(rangeDoppler)/2):], rangeDoppler[:int(len(rangeDoppler)/2)], axis=0)

                # Generate the range and doppler arrays for the plot
                rangeArray = np.array(range(configParameters["numRangeBins"]))*configParameters["rangeIdxToMeters"]
                dopplerArray = np.multiply(np.arange(-configParameters["numDopplerBins"]/2 , configParameters["numDopplerBins"]/2), configParameters["dopplerResolutionMps"])
                
                plt.clf()
                cs = plt.contourf(rangeArray,dopplerArray,rangeDoppler)
                fig.colorbar(cs, shrink=0.9)
                fig.canvas.draw()
                plt.pause(0.1)
       
        
        # Remove already processed data
        if idX > 0 and byteBufferLength > idX:
            shiftSize = totalPacketLen
                    
            byteBuffer[:byteBufferLength - shiftSize] = byteBuffer[shiftSize:byteBufferLength]
            byteBuffer[byteBufferLength - shiftSize:] = np.zeros(len(byteBuffer[byteBufferLength - shiftSize:]),dtype = 'uint8')
            byteBufferLength = byteBufferLength - shiftSize
            
            # Check that there are no errors with the buffer length
            if byteBufferLength < 0:
                byteBufferLength = 0
                

    return dataOK, frameNumber, detObj

# -------------------------    MAIN   -----------------------------------------  

# Configurate the serial port
CLIport, Dataport = serialConfig(configFileName)

# Get the configuration parameters from the configuration file
configParameters = parseConfigFile(configFileName)

    
   
# Main loop 
detObj = {}  
frameData = {}    
currentIndex = 0
fig = plt.figure()
while True:
    try:
        dataOk, frameNumber, detObj = readAndParseData16xx(Dataport, configParameters)
        
        if dataOk:
            # Store the current frame into frameData
            frameData[currentIndex] = detObj
            currentIndex += 1
        
        time.sleep(0.03) # Sampling frequency of 30 Hz
        
    # Stop the program and close everything if Ctrl + c is pressed
    except KeyboardInterrupt:
        CLIport.write(('sensorStop\n').encode())
        CLIport.close()
        Dataport.close()
        break