CN107466389B - 用于确定类型不可知的rf信号表示的方法和装置 - Google Patents
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Abstract
本文描述用于类型不可知的射频(RF)信号表示的技术和设备。这些技术和设备使得能够通过类型不可知的RF信号表示来使用多个不同类型的雷达系统和场。通过这样做，识别和应用层分析可以独立于在不同雷达系统和场之间不一样的各种雷达参数。
Description
相关申请的交叉引用
本申请要求2015年4月30日提交的美国临时专利申请No.62/155,357和2015年10月6日提交的美国临时专利申请No.62/237,750，其公开内容在此通过引用而全部并入本文。
背景技术
小屏幕计算设备继续激增，诸如智能电话和计算手镯、指环和手表。像许多计算设备一样，这些小屏幕设备通常使用虚拟键盘来与用户交互。但是，在这些小屏幕上，许多人发现通过虚拟键盘来交互很困难，因为这通常导致慢和不准确的输入。这使用户受到挫折且限制了小屏幕计算设备的适用性。该问题通过基于屏幕的手势识别技术而部分得到了解决。但是，由于这些屏幕的尺寸，这些基于屏幕的手势仍然面临大量可用性问题。
为了解决这个问题，光学手指和手跟踪技术已得到发展，其使得能够进行不在屏幕上进行的手势跟踪。但是，这些光学技术较大、昂贵或不准确，由此限制了它们在解决小屏幕计算设备的可用性问题方面的作用。
而且，通过手势来控制对于其他设备和使用来说继续激增，诸如从中到大距离。人们不仅希望控制靠近他们的设备，而且还希望控制那些中等到较大距离的设备，诸如跨过房间控制立体声音响、不同房间中的恒温器、或者几米远的电视。
发明内容
本文描述用于类型不可知的射频(RF)信号表示的技术和设备。这些技术和设备使得能够通过类型不可知的RF信号表示的标准集合来使用多个不同类型的雷达系统和场。通过这样做，识别和应用层分析可以独立于在不同雷达系统和场之间不一样的各种雷达参数。
通过这些技术和设备的使用，在手势的大小和与雷达传感器的距离这两个方面都可以使用较大范围的手势。即使例如具有不同雷达系统的单个设备，也可以利用独立于不同雷达系统的手势分析而识别这些手势。坐在沙发上控制电视、站在厨房控制烤箱或冰箱、距离计算手表的小屏幕显示器几厘米来控制应用的人的手势，或者甚至走出房间使得灯关闭的人的动作——所有这些都可以被识别而不需要构建特定于类型的的识别和应用层分析。
提供本发明内容以介绍关于类型不可知的RF信号表示的简化概念，其在下面的具体实施方式中进一步进行描述。本发明内容不旨在用于识别所要求保护的主题的本质特征，也不旨在被用于确定所要求保护主题的范围。
附图说明
结合下面的附图来描述用于类型不可知的RF信号表示的技术和设备的实施例。在全部附图中，相同附图标记用于指代相似特征和组件：
图1图示说明示例环境，在其中可以体现使能类型不可知的RF信号表示的技术。该环境图示说明了1到N不同特定于类型的的雷达系统、抽象模块和手势模块。
图2详细地图示说明图1的抽象模块的示例。
图3详细地图示说明图1的手势模块的示例。
图4图示说明计算设备，通过该计算设备可以使能类型不可知的RF信号表示的确定。
图5图示说明通过类型不可知的RF信号表示的确定而使能手势识别的示例方法。
图6图示说明图1的示例不同雷达场。
图7图示说明体现类型不可知的RF信号表示或在其中可以实现能够使用类型不可知的RF信号表示的技术的示例计算系统。
具体实施方式
概览
本文描述使能类型不可知的RF信号表示的技术和设备。这些技术和设备使能通过不同雷达类型或场所感应的大幅度的动作和手势，诸如使用、控制以及与从智能电话到冰箱的各种设备交互的手势。该技术和设备能够这样做而不需要构建特定于类型的识别和应用层分析。
考虑图1，其图示说明了示例环境100，其中可以体现使能类型不可知的RF信号表示的技术。环境100包括不同特定于类型的的雷达系统102，利用从1到N系统的某个数字来示出，标以特定于类型的雷达系统102-1、102-2和102-N。这些特定于类型的雷达系统102可以包括各种类型的雷达系统，其能够提供多种多样的雷达场，诸如单音(single tone)、步进调频、线性调频、冲激或啁啾。
这些特定于类型的雷达系统102中的每个通过不同结构或不同操作的雷达发射元件104(用104-1、104-2和104-N示出)而提供不同雷达场。这些雷达场可能与这里所标注的不同，并且可以具有不同的调制、频率、幅度或相位。这些特定于类型的雷达系统102中的每个还包括天线元件106，在某些情况下还包括预处理器108，都相应地标为天线元件106-1、106-2和106-N以及预处理器108-1、108-2和108-N。
这些特定于类型的雷达系统102中的每个发射雷达以提供雷达场110，随后从在雷达场110中运动的对象接收反射信号112。这里示出了三个人手，每个执行不同的手势，摇手手势114、摇拳手势116(美国符号语言(ASL)手势的“Yes”(是))以及捏手指手势118，尽管技术不限于人手或手势。
如所示，特定于类型的雷达系统102中的每个提供响应于接收到反射信号112的特定于类型的原始数据120(为视觉简洁，只有一个系统示出接收到反射信号112)。特定于类型的雷达系统102中的每个提供特定于类型的原始数据120，示为原始数据120-1、120-2和120-N，相应地用于每个系统。这些原始数据120中的每个都可以是，但不必是，原始数字采样，特定于类型的雷达系统102的预处理器108已经针对其执行了预处理。
这些特定于类型的原始数据120由抽象模块122接收。通常，抽象模块122将不同类型的特定于类型的原始数据120中的每个都变换成类型不可知的信号表示124，示出为类型不可知的信号表示124-1、124-2和124-N，相应地用于特定于类型的原始数据120-1、120-2和120-N中的每个。这些类型不可知的信号表示124随后由识别模块126接收。通常，识别模块126为类型不可知信号表示124中的每个确定在相应的两个或更多个不同雷达场内的对象的手势128或动作。这些手势128中的每个被示出为手势128-1、128-2和128-N，相应地用于类型不可知的信号表示124-1、124-2和124-N中的每个。利用所确定的手势128或动作，识别模块126将每个手势128或动作传递到另一实体，诸如在设备上执行的应用，以控制该应用。注意，在一些情况下，单个手势或动作被确定用于多个不同原始数据120，并因此用于多个不同类型不可知的信号表示124，诸如在两个雷达系统或场同时用于感应人在不同雷达场中的运动的情况下。抽象模块122的功能和能力作为图2的一部分并且识别模块126的功能和能力作为图3的一部分而更详细地描述。
示例抽象模块
图2图示说明图1的抽象模块122的示例。抽象模块122接收特定于类型的原始数据120中的一个或多个并且对于原始数据120-1、120-2直到120-N中的每个相应地输出类型不可知的信号表示124-1、124-2直到124-N。在一些情况下，原始数据120首先由原始信号处理器202处理，其被配置为基于特定于类型的原始数据120而提供复杂信号，其中复杂信号包含幅度和相位信息，从中可以提取和展开特定于类型的原始数据120的相位。对于冲激雷达(一种低功率超宽带雷达类型)，处理类型的示例包括平滑带通滤波和希尔伯特变换。对于调频连续波(FM-CW)雷达的处理包括窗滤波和范围快速(fast-time)傅里叶变换(FFT)。进一步，原始信号处理器202的处理可以被配置为脉冲形状滤波器和脉冲压缩双相相移键控(BPSK)雷达。
无论由原始信号处理器202处理还是作为特定于类型的原始数据120接收，信号变换器204用来将原始数据(处理过的等)变换为类型不可知的信号表示124。通常，信号变换器被配置为将原始数据捕捉的对象建模为散射中心集合，其中散射中心集合中的每个具有反射率，该反射率取决于进行运动以执行手势或动作的对象的形状、尺寸、方面或材料。为了这样做，信号变换器204可以从特定于类型的原始数据120提取对象属性和动力学作为散射中心集合的快速(fast-time)(例如，以每个采集(acquisition))和慢速(slow-time)(例如，以多个采集)或瞬态或后期电磁(EM)响应的函数。
这利用四个示例变换来图示说明，其可以单独使用或者结合使用。这些包括将数据变换为范围多普勒时间线型206、范围时间线型208、微多普勒线型210以及快速谱图212。范围多普勒时间线型206在范围和速度维度上分解散射中心。范围时间线型208是范围的时间历史的线型。微多普勒线型210是多普勒的时间历史的线型。快速谱图212识别依赖于频率/目标的信号衰落和谐振。这些变换中每个都是类型不可知的信号表示，尽管类型不可知的信号表示124可以包括每个中的一个或多个。
示例手势模块
如上所注意的，识别模块126的功能和能力作为图3的一部分更详细来描述。如所示，图3图示说明图1的识别模块126的示例，其包括特征提取器302和手势识别器304。通常，识别模块126接收类型不可知的信号表示124(利用1到N信号表示示出，尽管少到一个也可以被接收和识别)并基于类型不可知的信号表示124来确定从中确定类型不可知的信号表示124的相应的不同类型的特定于类型的雷达场内的对象的手势或动作。更具体地，特征提取器302被配置为提取类型不可知的特征，诸如信号变换、工程特征、计算机视觉特征、机器学习特征或者推断的目标特征。
更具体地，手势识别器304被配置为确定对象所执行的动作或手势，诸如走出房间、坐，或者换频道、关闭媒体播放器、或者关闭烤箱的手势。为了这样做，手势识别器304可以基于类型不可知的信号表示124或来自特征提取器302的提取后的特征来确定手势分类、运动参数跟踪、回归估计或手势概率。手势识别器304还可以将手势128映射为与对应用和/或设备306的控制输入相关联的配置前的控制手势。识别模块126随后传递每个确定的手势128(用1到N手势来示出，尽管少到一个也可以被确定)以便有效控制应用和/或设备306，诸如控制或更改显示器上的用户界面、设备的功能或能力。如图1中所示，这些手势可以包括人手的手势，诸如摇手手势114、摇拳手势116以及捏指手势118，仅举几个例子。
如上所注意的，用于确定类型不可知的RF信号表示的技术允许识别和应用层分析独立于在不同雷达系统和场之间不一样的各种雷达参数。这使得很少几个或没有图3的元件要特定于具体雷达系统。因此，识别模块126不需要特定于雷达场类型或者构建以适应一个或甚至任何类型的雷达场。进一步，应用和/或设备306不需要要求应用层分析。识别模块126以及应用和/或设备306可以因此通用于许多不同类型的雷达系统和场。
本文现在转到示例计算设备，在其中可以使用类型不可知的RF信号表示，随后是示例方法和示例雷达场，以示例计算系统为结束。
示例计算设备
图4图示说明计算设备，通过该计算设备可以使能类型不可知的RF信号表示。计算设备402被图示为各种非限制示例设备，桌面计算机402-1、计算手表402-2、智能电话402-3、平板402-4、计算指环402-5、计算眼镜402-6以及微波402-7，尽管其他设备也可以被使用，诸如家用自动化和控制系统、娱乐系统、音频系统、其他家用电器、安全系统、笔记本、汽车、以及电子阅读器。注意，计算设备402可以是可穿戴、不可穿戴但移动、或者相对不可移动(例如桌面和电器)。
计算设备402包括一个或多个计算机处理器404和计算机可读介质406，其包括存储器介质和存储介质。体现为计算机可读介质406上的计算机可读指令的应用和/或操作系统(未示出)可以由处理器404执行来提供这里所述的一些功能。计算机可读介质406还包括抽象模块122和识别模块126，且还可以包括它们的可选组件、原始信号处理器202、信号变换器204、特征提取器302和手势识别器304(如上所述)中的每个。
计算设备402还可以包括一个或多个网络接口408用于在有线、无线或光网络以及显示器410上传送数据。举例来说而并不是限制，网络接口408可以在局域网(LAN)、无线局域网(WLAN)、个域网(PAN)、广域网(WAN)、内联网、互联网、对等网络、点到点网络、网状网络等上传送数据。显示器410可以与计算设备402集成或者与之相关联，诸如与桌面计算机402-1集成或相关联。
计算设备402还被示出包括来自图1的一个或多个特定于类型的雷达系统102。如所注意的，这些特定于类型的雷达系统102每个都提供不同类型的雷达场110，无论由不同类型雷达发射元件104还是使用只不过一种类型的雷达发射元件104的不同方式，并且因此提供不同类型的原始数据120。
更具体地，不同类型的雷达场110可以包括连续波和脉冲雷达系统，以及用于闭合或远识别、或用于视线或遮挡使用的场。脉冲雷达系统通常具有更短发射时间和更高峰值功率，且包括冲激和啁啾雷达系统两种。脉冲雷达系统具有基于飞行时间的范围和基于频移的速度。啁啾雷达系统具有基于飞行时间的范围(脉冲压缩)和基于频移的速度。连续波雷达系统通常具有相对更长的发射时间和较低的峰值功率。这些连续波雷达系统包括单音、线性调频(FM)和步进FM类型。单音雷达系统具有基于相位的有限范围和基于频移的速度。线性FM雷达系统具有基于频移的范围和也基于频移的速度。步进FM雷达系统具有基于相位或飞行时间的范围和基于频移的速度。尽管这里提到了这五个类型的雷达系统，也可以使用其他类型，诸如正弦调制方案雷达系统。
这些雷达场110可以从诸如一至五十毫米的小尺寸，到半米至五米，到甚至一至大约三十米变化。在较大尺寸的场中，天线元件106可以被配置为接收和处理雷达场的反射以基于由身体、胳膊或腿的运动引起的来自人组织的反射而提供大身体手势，尽管也可以感应更小和更精确的手势。示例大尺寸雷达场包括在其中用户做出手势来从沙发控制电视、跨房间改变来自立体声音响的歌曲或音量、关闭烤箱或烤箱定时器(近场也将有用)、开或关房间中的灯等等。
还注意，特定于类型的雷达系统102可以同许多不同计算设备或外围一起使用或嵌入其中，诸如在家里的墙中以控制家用电器和系统(例如，自动控制面板)，在汽车中控制内部功能(例如，音量、巡航控制、或甚至驾驶汽车)，或者作为膝上型计算机的附件来控制膝上型计算机上的计算应用。
雷达发射元件104可以被配置为从距离计算设备或其显示器不远(如果有距离的话)处提供窄或宽雷达场，包括与波束扫描雷达场相对照的全连续场的雷达场。雷达发射元件104可以被配置为提供上面所阐述的各种类型的雷达。天线元件106被配置为接收雷达场的反射或感应雷达场中的交互。在一些情况下，反射包括来自雷达场内的人组织的反射，诸如手或胳膊的运动。天线元件106可以包括一个或许多天线或传感器，诸如辐射传感器的阵列，阵列中的数目基于所需分辨率以及该场是面(surface)还是体(volume)。
示例方法
图5描绘了使用类型不可知的RF信号表示来识别手势和动作的方法500。方法500从一个或多个不同类型的雷达场接收特定于类型的原始数据，随后将这些特定于类型的原始数据变换为类型不可知的信号表示，其随后被用来确定相应的不同雷达场内的手势或动作。该方法被示出为指定所执行的操作的块的集合，但不必限于为执行相应块的操作而示出的次序或组合。在下面讨论的部分中，可以对图1的环境100进行引用且作为图2或3中具体所述，对其的引用只是举例。技术不限于在一个设备上操作的一个实体或多个实体的执行。
更具体地，方法500在502接收表示两个或更多个反射信号的不同类型的特定于类型的的原始数据。这两个或更多不同反射信号，如上所注意的，每个都从在两个或更多个不同雷达场中的每个中运动的对象反射。这些反射信号可以在相同或几乎相同时间接收，用于两个雷达场中的一个运动，或者不同时间两个不同场中的两个不同运动。这些不同运动和时间可以包括例如两个手指的微运动以控制智能手表以及大手势以控制另一房间中的立体声音响，以及今天做的一个运动和昨天的另一个。尽管不同类型的雷达系统在图1中图示，不同雷达场可以通过遵循两个或更多个调制方案的甚至相同雷达系统来提供。
举例来说，考虑四个不同雷达场110，在图6的雷达场602、604、606、610和612示出。尽管难以示出调制方案的颗粒度水平等等方面的差异，图6图示说明了从近到远以及从高分辨率到低分辨率等等的这些雷达场的不同应用中的一些。雷达场602、604和606包括三个类似的雷达场，用于检测用户动作和手势，诸如走进或走出房间、做出大手势以操作电视或计算机上的游戏以及小手势来控制恒温器或烤箱。雷达场608示出较小的场，用于用户不佩戴手表的另一手对计算手表的控制。雷达场610示出非体积雷达场，用于用户佩戴计算手表的手的控制。雷达场612示出中等尺寸的雷达场，使得能够对大约1/2到3米远的计算机进行控制。
这些雷达场602到612使得用户能够用中断雷达场的他或她的胳膊、身体、一个或多个手指、一个或多个手(或者例如触笔的设备)执行复杂或简单的手势。示例手势包括可以与当前的触敏显示器一起使用的许多手势，诸如扫、两指捏、伸展、旋转、轻敲等等。其他复杂的或虽然简单但是三维的手势也可被使能，示例包括许多符号语言手势，例如美国符号语言(ASL)和世界范围的其他符号语言中的那些。这些中的几个示例是：上下摇拳，在ASL中表示“是”(Yes)；打开食指而中指移动到连接打开的拇指，表示“否”(No)；平摊手向上移动一步，表示“前进”(Advance)；平摊且成角度的手上下移动，表示“下午”(Afternoon)；紧握手指而打开拇指移动到打开手指和打开的拇指，表示“出租车”(taxicab)；食指大致垂直方向上向上移动，表示“上”(up)等等。但这些只是可以被感应且映射到特定设备或应用的许多手势中的几个，诸如前进手势用来跳过基于web的电台应用上的另一歌曲、在立体声音响上播放的压缩盘上的下一首歌曲、或者计算机显示器或数字相框上的文件或影集中的下一页或图像。
回到图5，在504，方法500将不同类型的特定于类型的原始数据中的每个变换为类型不可知的信号表示。如上所注意的，这些变换可以通过确定范围多普勒时间线型506、确定范围时间线型508、确定微多普勒线型510、以及确定快速谱图512来进行。这些作为图2描述的一部分而更详细来描述。
在514，方法500对于在操作504创建的两个或更多个类型不可知的信号表示中的每个确定在相应的两个或更多个不同雷达场内的对象的手势或动作。
注意，在两个或更多个不同雷达场的每个中进行运动的对象可以是进行相同动作的相同对象。在这样的情况下，两个不同类型的雷达场被用于改善手势识别、鲁棒性、分辨率等等。因此，确定对象运动所执行的手势或动作在此情况下同时基于两个或更多个类型不可知的信号表示。
在516，方法500将所确定的手势或动作中的每个传递到应用或设备以便有效控制或更改与应用相关联的显示器、功能或能力。
示例计算系统
图7图示说明可以实现为如上结合之前的图1-6所描述的任何类型的客户端、服务器和/或计算设备以实现类型不可知的RF信号表示的示例计算系统700的各种组件。
计算系统700包括通信设备702，其使能设备数据704(例如，接收到的数据、正在接收的数据、被调度用于广播的数据、数据的数据分组等等)的有线和/或无线通信。设备数据704或其他设备内容可以包括设备的配置设置、存储在设备上的媒体内容、和/或与设备的用户相关联的信息(例如，执行手势的动作者的身份)。存储在计算系统700上的媒体内容可以包括一个或多个数据输入706，经由该数据输入，任何类型数据、媒体内容和/或输入可以被接收，诸如人的话语、与雷达场的交互、用户可选的输入(明确或隐含)、消息、音乐、电视媒体内容、记录的视频内容、以及从任何内容和/或数据源接收到的任何其他类型的音频、视频和/或图像数据。
计算系统700还包括通信接口708，其可以被实现为串行和/或并行接口、无线接口、任何类型的网络接口、调制解调器中的任何一个或多个、以及实现为任何其他类型的通信接口。通信接口708提供计算系统700和通信网络之间的连接和/或通信链接，其他电子、计算和通信设备由此与计算系统700通信数据。
计算系统700包括一个或多个处理器710(例如微处理器、控制器等中任意一个)，其处理各种计算机可执行指令来控制计算系统700的操作并使能用于或在其中可以体现类型不可知的RF信号表示的技术。可替选地或此外，计算系统700可以用关于通常在712识别的处理和控制电路而实现的硬件、固件或固定逻辑电路中的任何一个或组合来实现。尽管未示出，计算系统700可以包括系统总线或数据传输系统，其耦合设备内的各种组件。系统总线可以包括不同总线结构中的任何一个或组合，诸如存储器总线或存储器控制器、外围总线、通用串行总线和/或利用各种总线架构中任何架构的处理器或局部总线。
计算系统700还包括计算机可读介质714，诸如一个或多个存储器设备，其使能永久和/或非瞬时数据存储(即，与仅仅信号传输相对照)，其示例包括随机存取存储器(RAM)、非易失性存储器(例如，只读存储器(ROM)、闪存存储器、EPROM、EEPROM等等中的任何一个或多个)以及盘存储设备。盘存储设备可以被实现为任何类型的磁或光存储设备，诸如硬盘驱动器、可记录和/或可覆写压缩盘(CD)、任何类型的数字多用途盘(DVD)等。计算系统700还可以包括大容量存储介质设备(存储介质)716。
计算机可读介质714提供数据存储机制以存储设备数据704，以及各种设备应用718以及与计算系统700的操作方面相关的任何其他类型的信息和/或数据。例如，操作系统720可以利用计算机可读介质714而被保持作为计算机应用并在处理器710上执行。设备应用718可以包括设备管理器，诸如任何形式的控制应用、软件应用、信号处理和控制模块、特定设备的本地的代码、抽象模块或手势模块等等。设备应用718还包括系统组件、引擎或管理器来实现类型不可知的RF信号表示，诸如抽象模块122和识别模块126。
计算系统700还可以包括，或者可以访问，一个或多个特定于类型的雷达系统102，包括雷达发射元件104和天线元件106。尽管未示出，抽象模块122或识别模块126的一个或多个元件可以整体或部分通过硬件来操作，诸如整体或部分与特定于类型的雷达系统102集成。
结论
尽管使用类型不可知的RF信号表示的技术以及包括类型不可知的RF信号表示的装置已经被描述为特定于特征和/或方法的语言，应该理解，所附权利要求的主题不必限制为所述的特定特征或方法。而是，特定特征和方法被公开作为确定类型不可知的RF信号表示的方式的示例实现。
Claims (17)
1.其上存储有指令的至少一个非暂时性计算机可读存储介质，所述指令响应于由至少一个计算机处理器执行而使得所述计算机处理器：
接收表示由对象在特定于类型的雷达场内的运动所导致的反射信号的特定于类型的原始数据；以及
将所述特定于类型的原始数据变换为独立于所述特定于类型的雷达场的参数的类型不可知的信号表示，所述类型不可知的信号表示包括用于所述特定于类型的原始数据的范围多普勒时间线型、范围时间线型、微多普勒线型或者快速谱图，所述变换是根据作为散射中心集合的对象的模型的；以及
基于所述类型不可知的信号表示，确定由所述对象所执行的手势或动作。
2.如权利要求1所述的非暂时性计算机可读存储介质，其中：
所述指令进一步使得所述计算机处理器基于所述特定于类型的原始数据而接收复杂信号，所述复杂信号具有幅度和相位信息，从所述幅度和相位信息能够提取和展开所述特定于类型的的原始数据的相位；以及
所述类型不可知的信号表示是基于所述特定于类型的原始数据的相位。
3.如权利要求1所述的非暂时性计算机可读存储介质，其中：
所述指令进一步使得所述计算机处理器从所述类型不可知的信号表示中提取类型不可知的特征，所述类型不可知的特征包括信号变换、工程特征、计算机视觉特征、机器学习特征或者推断的目标特征；以及
由所述对象执行的所述手势或动作的确定是基于所述类型不可知的特征的。
4.如权利要求1所述的非暂时性计算机可读存储介质，其中：
所述指令进一步使得所述计算机处理器确定手势分类、运动参数跟踪、回归估计或手势概率；以及
由所述对象执行的所述手势或动作的确定是基于所述手势分类、运动参数跟踪、回归估计或手势概率。
5.如权利要求1所述的非暂时性计算机可读存储介质，其中：
所述指令进一步使得所述计算机处理器：
接收表示由所述对象在另一个特定于类型的雷达场内的运动导致的另一个反射信号的其它类型不可知的原始数据；以及
将所述其它特定于类型的原始数据变换为另一个类型不可知的信号表示；以及
由所述对象执行的所述手势或动作的确定是进一步基于所述其它类型不可知的信号表示。
6.如权利要求1所述的非暂时性计算机可读存储介质，其中，所述特定于类型的雷达场的所述参数包括调制、频率、幅度或相位参数。
7.如权利要求1所述的非暂时性计算机可读存储介质，其中，所述参数包括是单音、步进调频、线性调频、冲激或啁啾的所述特定于类型的雷达场。
8.一种计算机实现的方法，包括：
接收表示由对象在特定于类型的雷达场内的运动导致的反射信号特定于类型的原始数据；
将所述特定于类型的原始数据变换成独立于所述特定于类型的雷达场的参数的类型不可知的信号表示，所述类型不可知的信号表示包括用于所述特定于类型的原始数据的范围多普勒时间线型、范围时间线型、微多普勒线型或者快速谱图，所述变换是根据作为散射中心集合的对象的模型的；
基于所述类型不可知的信号表示，确定由所述对象所执行的手势或动作；以及
将所确定的手势或动作传递到应用以便有效控制或更改与所述应用相关联的显示、功能或能力。
9.如权利要求8所述的计算机实现的方法，其中，所述类型不可知的信号表示独立于所述特定于类型的雷达场的调制、频率、幅度或相位。
10.如权利要求8所述的计算机实现的方法，其中，所述类型不可知的信号表示独立于是单音、步进调频、线性调频、冲激或啁啾的所述特定于类型的雷达场。
11.如权利要求8所述的计算机实现的方法，进一步包括基于所述特定于类型的原始数据而接收复杂信号，所述复杂信号具有幅度和相位信息，从所述幅度和相位信息能够提取和展开所述特定于类型的的原始数据的相位；以及
其中，所述类型不可知的信号表示是基于所述特定于类型的原始数据的相位。
12.如权利要求8所述的计算机实现的方法，进一步包括确定手势分类、运动参数跟踪、回归估计或手势概率；以及
由所述对象执行的所述手势或动作的确定是基于所述手势分类、运动参数跟踪、回归估计或手势概率。
13.一种装置，包括：
至少一个计算机处理器；
特定于类型的雷达系统，被配置为提供特定于类型的雷达场，所述特定于类型的雷达场通过调制方案或一种类型的硬件雷达发射元件来提供，所述特定于类型的雷达系统包括：
至少一个雷达发射元件，被配置为提供所述特定于类型的雷达场；以及
至少一个天线元件，被配置为接收由在所述特定于类型的雷达场中运动的对象导致的反射信号；以及
其上存储有指令的至少一个计算机可读存储介质，所述指令响应于由所述计算机处理器执行而使得所述计算机处理器：
接收表示由对象在所述特定于类型的雷达场内的运动所导致的反射信号的特定于类型的原始数据；
将所述特定于类型的原始数据变换为独立于所述特定于类型的雷达场的参数的类型不可知的信号表示，所述类型不可知的信号表示包括范围多普勒线型、范围线型、微多普勒线型或者快速谱图，所述变换是根据作为散射中心集合的对象的模型的，以及
基于所述类型不可知的信号表示，确定由所述对象执行的手势或动作；以及
将所确定的手势或动作传递到应用以便有效控制或更改与所述应用相关联的显示、功能或能力。
14.如权利要求13所述的装置，其中：
所述指令进一步使得所述处理器基于所述特定于类型的原始数据而接收复杂信号，所述复杂信号具有幅度和相位信息，从所述幅度和相位信息能够提取和展开所述特定于类型的的原始数据的相位；以及
所述类型不可知的信号表示是基于所述特定于类型的原始数据的相位。
15.如权利要求13所述的装置，其中：
所述指令进一步使得所述处理器确定手势分类、运动参数跟踪、回归估计或手势概率；以及
由所述对象执行的所述手势或动作的确定是基于所述手势分类、运动参数跟踪、回归估计或手势概率。
16.如权利要求13所述的装置，其中，所述装置是具有显示器的移动计算设备。
17.如权利要求16所述的装置，其中，所确定的手势或动作是控制与所述应用相关联的用户界面并且呈现在所述显示器上的手势。
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