Ibeacon一维小项目

概述

这个项目主要是定位50米走廊的位置，共有5个Ibeacon设备，每隔10米放置一个。显示也不像之前放在pc端上显示，而是实时显示在手机屏幕上。Android扫描到Ibeacon设备的RSSi后，先进行卡尔曼滤波，得到一个相对稳定的RSSI，再根据可调的距离算法（该距离算法是买IBeacon设备厂家提供的算法，其实也是一个衰减模型）获得距离。距离进行sma平滑后，通过5个ibeacon设备相互迭代，得到坐标。

需要源码的小伙伴：留言
最近太忙，不能一一回复最新的程序。
需要的可以看看最初的demo：https://github.com/zhoudatang/SimpleIbeacon。

Appconfig类

该类是APP所有配置的配置类，可以根据实际环境，调节这个类。配置内容有：绘图坐标点大小，蓝牙扫描时间，5个ibeacon部署位置，sma平滑精度，卡尔曼算法的误差调节以及距离衰减模型的参数调节。（注意：：使用时候，由于beacon设备uuid，蓝牙地址等不同，需要在ibeacondevice中，更改你们的ibeacon设备的uuid，major，minor，以及蓝牙地址，否者不会识别你们的beacon设备）如下：代码

public class AppConfig {/*MAIN_ACTIVITY*/static private  int MAIN_ACTIVITY_SCAN_TIME=3000;/*POINT*/static private  int POINT_RADIUS=25;//绘制点半径/*CALMAN*/static private double KALMAN_Q1=16; //卡尔曼预测误差的方差static private double KALMAN_R1=100; //卡尔曼噪声误差的方差

Point类

存储坐标点的数据类

public class Point {//点的X坐标private int x;//点的Y坐标private int y;//点的半径，默认为10像素private int radius = AppConfig.getPointRadius();public Point(int x, int y) {this.x = x;this.y = y;}public Point(int x, int y, int radius) {this.x = x;this.y = y;this.radius = radius;}public int getX() {return x;}
.......
}

queue类

一个自己写的队列类,用于sma平滑数据，队列没满则会一直放即时的距离值进去，满了则计算队列（默认5个值）的平均数，为当前的距离值，然后出一个值，再进最新值

public class queue {private float[] data ;// 队列private int front;// 队列头，允许删除private int rear;// 队列尾，允许插入private int LENGTH=AppConfig.getQueueLength();private int full=0;private int t=0;//判断队列是否装满private  int relute=0;public queue() {data = new float[LENGTH];front = rear = 0;}// 入队public void offer(float date) {if (rear>=LENGTH){rear=0;}data[rear++] = date;if (t++>=LENGTH){full=1;//relute=(int)(data[0]+data[1]+data[2]+data[3]+data[4])/5;for (int i=0;i<LENGTH;i++){relute=0;relute += data[i];}}}// 出队public float poll() {if (front<LENGTH){float value = data[front];// 保留队列的front端的元素的值front++;return value;}else{front=0;float value = data[front];return  value;}}public boolean full(){if (full==1)return  true;elsereturn false;}public int getRelute() {return relute;}
}

ibeacondevice类

该类是五个Ibeacon设备数据的类，存放五个Ibeacon的uuid，蓝牙地址等信息

public class IbeaconDevice {public int major;public int minor;public String proximityUuid;public String bluetoothAddress;int x;int y;public  IbeaconDevice(String bluetoothAddress,int x,int y){this.bluetoothAddress=bluetoothAddress;this.x=x;this.y=y;major=10;minor=7;proximityUuid="fda50693-a4e2-4fb1-afcf-c6eb07647825";}public int getMajor() {return major;}public int getX() {return x;}public int getY() {return y;}

ibeacon类

该类存放扫描获得的实时beacon对象，与ibeacondevice最大的区别在于RSSI

public class iBeacon {public String name;public int major;public int minor;public String proximityUuid;public String bluetoothAddress;public int txPower;public int rssi;public double distance=0;public int x;public int y;
}

Mainactivity类

UI界面，主要进行图像的显示和蓝牙的扫描。
敲击扫描按钮，开始扫描

 //开启蓝牙扫描findViewById(R.id.mStartBtn).setOnClickListener(new View.OnClickListener() {@Overridepublic void onClick(View v) {mBLE.startLeScan(mScanCallback);}});

将我的蓝牙显示的函数：

    private void getBlueToothDetail() {if (mBLE == null) return;mBluetoothAdapter = mBLE.getBluetoothAdapter();if (mBluetoothAdapter == null) return;Textview1.setText("我的蓝牙：" + mBluetoothAdapter.getName() + "\n地址：" + mBluetoothAdapter.getAddress());}

对了，这次使用的扫描是使用的第三方库，扫描更快更稳定，如下是扫描的回调

   private PeriodScanCallback mScanCallback = new PeriodScanCallback(TIME_OUT_SCAN) {@Overridepublic void onLeScan(BluetoothDevice device, int rssi, byte[] scanRecord) {logDevice(device, rssi, scanRecord);}@Overridepublic void onScanTimeout() {mBLE.startLeScan(mScanCallback);toast("扫描超时");}};private void logDevice(BluetoothDevice device, int rssi, byte[] scanRecord) {ibeacon = iBeaconClass.fromScanData(device, rssi, scanRecord,sma1);//先通过ibeaconclass获得ibeacon类if (ibeacon == null) return;Textview1.setText("\n" +"蓝牙地址"+ibeacon.bluetoothAddress);Textview1.append("\n" + "rssi" + ibeacon.rssi);Textview1.append("\n" + "distance" + ibeacon.distance);double t=mtwoPointAlgorithm.algorithm(ibeacon);Textview1.append("\nt=="+t);mPointView.drawPoint(new Point(mPointView.getWidth()/2+30,(int)((1-t/50)*mPointView.getHeight())));//绘制坐标，x坐标默认是图像宽度的一半。走道使用x,y和只使用y差距不大}

Ibeaconclass类

主要是将获得的广播数据，解析出一个ibeacon类对象。在最开始，会调用卡尔曼算法的类，先过滤RSSi值。

class iBeaconClass {static Kalman kalman1=new Kalman(AppConfig.getKalmanQ1(),AppConfig.getKalmanR1());//5个卡尔曼滤波器分别对5个ibeacon滤波static Kalman kalman2=new Kalman(AppConfig.getKalmanQ1(),AppConfig.getKalmanR1());static Kalman kalman3=new Kalman(AppConfig.getKalmanQ1(),AppConfig.getKalmanR1());static Kalman kalman4=new Kalman(AppConfig.getKalmanQ1(),AppConfig.getKalmanR1());static Kalman kalman5=new Kalman(AppConfig.getKalmanQ1(),AppConfig.getKalmanR1());static IbeaconDevice dev1 = new IbeaconDevice("88:3F:4A:EA:50:8E", 0, AppConfig.getBeaconDevice1Y());static IbeaconDevice dev2 = new IbeaconDevice("88:3F:4A:EA:4D:CE", 0, AppConfig.getBeaconDevice2Y());static IbeaconDevice dev3 = new IbeaconDevice("88:3F:4A:EA:4D:D6", 0, AppConfig.getBeaconDevice3Y());static IbeaconDevice dev4 = new IbeaconDevice("88:3F:4A:EA:4D:B3", 0, AppConfig.getBeaconDevice4Y());static IbeaconDevice dev5 = new IbeaconDevice("88:3F:4A:EA:50:85", 0, AppConfig.getBeaconDevice5Y());//解析数据static iBeacon fromScanData(BluetoothDevice device, int rssi, byte[] scanData,sma sma1) {// rssi=sma1.run(device.getAddress(),rssi);//平滑数据算法//卡尔曼滤波if (device.getAddress().equals(iBeaconClass.dev1.bluetoothAddress))rssi=(int)iBeaconClass.kalman1.KalmanFilter((double) rssi);if (device.getAddress().equals(iBeaconClass.dev2.bluetoothAddress))rssi=(int)iBeaconClass.kalman2.KalmanFilter((double) rssi);if (device.getAddress().equals(iBeaconClass.dev3.bluetoothAddress))rssi=(int)iBeaconClass.kalman3.KalmanFilter((double) rssi);if (device.getAddress().equals(iBeaconClass.dev4.bluetoothAddress))rssi=(int)iBeaconClass.kalman4.KalmanFilter((double) rssi);if (device.getAddress().equals(iBeaconClass.dev5.bluetoothAddress))rssi=(int)iBeaconClass.kalman5.KalmanFilter((double) rssi);//这个类代码很多。。。。。。。

sma类

简单平均算法，用来平滑滤波后得到的距离。

public class sma {IbeaconDevice dev1, dev2, dev3, dev4, dev5;public ArrayList<queue> arr_queue;//存放 5个ibeacon的动态数组 每个队列有5个值public  ArrayList<IbeaconDevice> arr_ineacon_device;sma(){arr_queue=new ArrayList<>();arr_ineacon_device=new ArrayList<>();dev1 = new IbeaconDevice("88:3F:4A:EA:50:8E", 0, AppConfig.getBeaconDevice1Y());dev2 = new IbeaconDevice("88:3F:4A:EA:4D:CE", 0,  AppConfig.getBeaconDevice2Y());dev3 = new IbeaconDevice("88:3F:4A:EA:4D:D6", 0,  AppConfig.getBeaconDevice3Y());dev4 = new IbeaconDevice("88:3F:4A:EA:4D:B3", 0,  AppConfig.getBeaconDevice4Y());dev5 = new IbeaconDevice("88:3F:4A:EA:50:85", 0,  AppConfig.getBeaconDevice5Y());arr_queue.add(new queue());arr_queue.add(new queue());arr_queue.add(new queue());arr_queue.add(new queue());arr_queue.add(new queue());arr_ineacon_device.add(dev1);arr_ineacon_device.add(dev2);arr_ineacon_device.add(dev3);arr_ineacon_device.add(dev4);arr_ineacon_device.add(dev5);}public  int run(String address,int rssi){if (address.equals(dev1.bluetoothAddress)){arr_queue.get(0).offer(rssi);return 0;}else if (address.equals(dev2.bluetoothAddress)){arr_queue.get(1).offer(rssi);return 0;}else if (address.equals(dev3.bluetoothAddress)){arr_queue.get(2).offer(rssi);return 0;}else if (address.equals(dev4.bluetoothAddress)){arr_queue.get(3).offer(rssi);return 0;}else if (address.equals(dev5.bluetoothAddress)){arr_queue.get(4).offer(rssi);return 0;}else {return 0;}}

Kalman类

使用的是之前写好的类

卡尔曼类

Algorithm类

类中有，在滤波和平滑后进行的迭代，两点距离算法，最后获得的是显示的坐标。外部调用algorithm，并传入一个即时ibeacon值，先判断队列是否满了（sma算法），满了则执行迭代算法。

public double algorithm(iBeacon now_ibeacon) {sma1.run(now_ibeacon.bluetoothAddress,now_ibeacon.rssi);//入队double buff=0;int temp=0;for(int i=0;i<5;i++)//循环遍历5个队列{if(sma1.arr_queue.get(i).full())//如果大于5){for (int j = i + 1; j < 5; j++)if (sma1.arr_queue.get(j).full())//如果大于5{buff+=twopoint(sma1.arr_ineacon_device.get(i),sma1.arr_ineacon_device.get(j),sma1.arr_queue.get(i).getRelute(),sma1.arr_queue.get(j).getRelute());temp++;}}}buff=buff/temp;return buff;}public  double twopoint(IbeaconDevice now_ibeacon,IbeaconDevice last_ibeacon,double now_dis,double last_dis){double relute = 0;double buf1, buf2;if (now_dis + last_dis > Math.abs(now_ibeacon.y - last_ibeacon.y))//如果是在两点外{if (now_ibeacon.y > last_ibeacon.y)//now是距离更远的信标{buf1 = now_ibeacon.y + now_dis;buf2 = last_ibeacon.y + last_dis;relute = (buf1 + buf2) / 2;} else//now是距离更近的信标{buf1 = now_ibeacon.y - now_dis;buf2 = last_ibeacon.y - last_dis;relute = (buf1 + buf2) / 2;}} else//在两点内{if (now_ibeacon.y > last_ibeacon.y)//now是距离更远的信标{buf1 = now_ibeacon.y - now_dis;buf2 = last_ibeacon.y + last_dis;relute = (buf1 + buf2) / 2;} else//last是距离更远的信标{buf1 = now_ibeacon.y + now_dis;buf2 = last_ibeacon.y - last_dis;relute = (buf1 + buf2) / 2;}}return relute;}

PointImageView类

用来显示的类

public class PointImageView extends AppCompatImageView {public PointImageView(Context context) {super(context);}public PointImageView(Context context, AttributeSet attrs) {super(context, attrs);}public PointImageView(Context context, AttributeSet attrs, int defStyleAttr) {super(context, attrs, defStyleAttr);}private Point mPoint = null;private Paint mPointPaint = new Paint();@Overrideprotected void onDraw(Canvas canvas) {super.onDraw(canvas);mPointPaint.setColor(Color.RED);if (mPoint != null) {canvas.drawCircle(mPoint.getX(), mPoint.getY(), mPoint.getRadius(), mPointPaint);}}public void drawPoint(Point p) {mPoint = p;invalidate();}