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AlphaBetaFilter

Alpha-beta filter for object tracking

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描述

TheAlphaBetaFilterobject represents an alpha-beta filter designed for object tracking. Use this tracker for platforms that follow a linear motion model and have a linear measurement model. Linear motion is defined by constant velocity or constant acceleration. Use the filter to predict the future location of an object, to reduce noise for a detected location, or to help associate multiple objects with their tracks.

Creation

Syntax

abf =字母足动
ABF = Alphabetafilter（名称，值，...）

描述

abf= AlphaBetaFiltercreates an alpha-beta filter for a discrete time, 2-D constant velocity system. The motion model of the filter corresponds to setting theMotionModelproperty to'2D Constant Velocity'。在这种情况下，过滤状态采用表单[X;vx;y;vy]。

example

abf= Alphabetafilter（名称，值，...）specifies the properties of the filter using one or moreName,Valuepair arguments. Any unspecified properties take default values.

Properties

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目标运动模型, specified as a character vector or string. Specifying1D,2D或者3D设置目标运动的尺寸。指定恒定速度assumes that the target motion has constant velocity at each simulation step. Specifying恒定加速假设目标运动在每个模拟步骤下都具有恒定加速度。

Data Types:char|string

过滤状态, specified as a scalar or a real-valuedM- 元素矢量。标量输入扩展到M- 元素矢量。The state vector is the concatenated states from each dimension.

The state vectors for each motion model are column vectors:

MotionModel属性 国家向量
'1D Constant Velocity' [X;vx]
'2D Constant Velocity' [X;vx;y;vy]
'3D Constant Velocity' [X;vx;y;vy;z; vz]
'1D Constant Acceleration' [X;vx;斧头]
'2D恒定加速度' [X;vx;斧头;y;vy;是]
'3D Constant Acceleration' [X;vx;斧头;y;vy;ay; z; vz; az]

例如，在哪里vx表示速度的x-direction andax表示加速x-方向。

例子：[200; 0.2; 150; 0.1; 0; 0.25]

Data Types:双倍的

State error covariance, specified as anM-经过-Mmatrix whereM是过滤状态的大小。标量输入扩展到M-经过-Mmatrix. The covariance matrix represents the uncertainty in the filter state.

例子：eye(6)

Process noise covariance, specified as a scalar or anD-经过-Dmatrix whereD是the dimensionality of motion. For example, ifMotionModel是'2D Constant Velocity, thenD= 2. A scalar input is extended to anD-经过-Dmatrix.

例子：[20 0.1; 0.1 1]

测量噪声协方差，指定为标量或D-经过-Dmatrix whereD是the dimensionality of motion. For example, ifMotionModel是'2D Constant Velocity, thenD= 2. A scalar input is extended to anM-经过-Mmatrix.

例子：[20 0.1; 0.1 1]

alpha-beta滤波器系数，指定为真实值的标量或行向量。任何标量输入都扩展到行向量。如果在MotionModelproperty, the coefficients are[alpha beta]。If you specify constant acceleration in theMotionModelproperty, the coefficients are[alpha beta gamma]。

例子：[20 0.1]

Object Functions

预测 预测状态和州估计误差协方差
correct Correct the state and state estimation error covariance
distance Distances between measurements and predicted measurements
可能性 Likelihood of measurement
clone Create identical object

例子

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打开实时脚本

应用α-β滤波器以跟踪沿X轴恒定速度移动的目标。

t = 0.1;v0 = 100;n = 100;plat =分阶段。平台（'MotionModel','Velocity',。。。'VelocitySource','Input port','初始位置',[100;0;0]); abfilt = phased.AlphaBetaFilter('MotionModel','1D Constant Velocity'）；Z = zeros(1,N); Zp = zeros(1,N); Zc = zeros(1,N);form = 1:N pos = plat(T,[100+20*randn;0;0]); Z(m) = pos(1); [~,~,Zp(m)] = predict(abfilt,T); [~,~,Zc(m)] = correct(abfilt,Z(m));endt = t (0: n - 1) *;情节(t, Z, t,Zp,t,Zc) xlabel(“时间）”）ylabel（'Position (m)') legend(“真轨道”,“预测轨道”,'Corrected Track',。。。'地点','Best')

图包含一个轴对象。轴对象包含3个类型行的对象。这些对象代表真实的轨道，预测的轨道，校正了轨道。

打开实时脚本

Apply the alpha-beta filter to track a target moving at constant acceleration along the x-axis.

t = 0.1;A0 = 100;n = 100;plat =分阶段。平台（'MotionModel','Acceleration',。。。'AccelerationSource','Input port','初始位置',[100;0;0]); abfilt = phased.AlphaBetaFilter(。。。'MotionModel','1D Constant Acceleration',。。。'Coefficients',[0.5 0.5 0.1]); Z = zeros(1,N); Zp = zeros(1,N); Zc = zeros(1,N);form = 1:N pos = plat(T,[100+20*randn;0;0]); Z(m) = pos(1); [~,~,Zp(m)] = predict(abfilt,T); [~,~,Zc(m)] = correct(abfilt,Z(m));endt = t (0: n - 1) *;情节(t, Z, t,Zp,t,Zc) xlabel(“时间）”）ylabel（'Position (m)'）；传奇（“真轨道”,“预测轨道”,'Corrected Track',。。。'地点','Best'）；

图包含一个轴对象。轴对象包含3个类型行的对象。这些对象代表真实的轨道，预测的轨道，校正了轨道。

打开实时脚本

应用Alpha-Beta滤波器以在三个维度上以恒定速度移动目标。

t = 0.1;v0 = 100;n = 100;plat =分阶段。平台（'MotionModel','Velocity',。。。'VelocitySource','Input port','初始位置',[100;0;0]); abfilt = phased.AlphaBetaFilter('MotionModel',。。。'3D Constant Velocity','状态',zeros(6,1)); Z = zeros(3,N); Zp = zeros(3,N); Zc = zeros(3,N);form = 1:N Z(:,m) = plat(T,[V0+20*randn;0;0]); [~,~,Zp(:,m)] = predict(abfilt,T); [~,~,Zc(:,m)] = correct(abfilt,Z(:,m));endt = t (0: n - 1) *;图（t，z（1，:)，t，zp（1，:)，t，zc（1，:)）xlabel（“时间）”）ylabel（'Position along X (m)') legend(“真轨道”,“预测轨道”,'Corrected Track',。。。'地点','Best')

图包含一个轴对象。轴对象包含3个类型行的对象。这些对象代表真实的轨道，预测的轨道，校正了轨道。

Extended Capabilities

C/C ++代码生成
使用MATLAB®CODER™生成C和C ++代码。

Version History

Introduced in R2018b