Android GPS数据获取和过滤，如何改善位置信息 [英] Android GPS data obtaining and filtering, how it improve location info

问题描述

我开始在Android 2.1(HTC Hero)上处理gps数据，并四处寻找有关卡尔曼滤波器和适合位置数据的最小二乘的主题.使用电话接收和记录GPS数据时，我发现如果保持在原位，则色散很小，但是移动时坐标非常准确.问题来了:-getLatitude()和getLongitude()函数是否提供原始"坐标，或者数据已被android预先过滤(位置固定或移动过程中)?

I'm starting to deal with gps data on Android 2.1 (HTC Hero) and look around on topics about Kalman filter and least squares fit to location data. While receiving and logging GPS data using phone I've found small dispersion if staying on position, but coordinates are pretty accurate when moving. Here comes the question: - Do getLatitude() and getLongitude() functions provide "raw" coordinates, or data was pre-filtered by android (while position is fixed or during movement)?

我很好奇是否有人在android上测试了Kalman，并且可以说您在gps方面有某些改进.以我为例，我每3秒读取一次GPS数据(已完成将其与指南针数据和加速度计一起通过移动网络发送到服务器的操作).因此，我可以在设备或服务器上进行过滤.如果要这样做，则可以更经常地进行设备读取，但是在服务器上，我可以使用额外的计算能力.

I'm curious if anyone tested Kalman on android and it's possible to say that you have certain improvements with gps. In my case I read GPS data every 3 seconds(was done to send it over mobile network to server along with compass data and accelerometer). Therefore, I can make filtering on device or on the server. If to do it on device reading can be done more often, but on server I could use additional calculation power.

推荐答案

我在自己的领域使用卡尔曼滤波器.卡尔曼滤波器是一种基于系统模型提高传感器集合的质量的滤波器.如果要实现卡尔曼滤波器，则需要第二个传感器，例如速度传感器或其他传感器.

I work with Kalman filters in my field. A Kalman filter is a filter that improves quality of a collection of sensors based on a system model. If you're trying to implement a Kalman filter, to do it, you'd need a second sensor, like a velocity sensor or etc.

您不会在Android软件包本身的传感器上取得任何进展.现代GPS芯片已经进行了广泛的过滤，其数据与不增加硬件就可以得到的数据一样好.特别是加速度计和指南针不足以计算出良好的速度数据，如果仅在3秒内对其进行采样，则绝对不能.糟糕的Kalman过滤器实现是真正固定数据集的好方法.

You're not going to make any progress with the sensors on the Android package itself. Modern GPS chips already do extensive filtering and the data is about as good as you're going to get it without adding hardware. The accelerometers and compass especially simply aren't good enough to compute good velocity data out of, and absolutely not if you're only sampling them at 3 seconds. A poor Kalman filter implementation is a great way to really screw up a dataset.

很抱歉，我个人认为您正在浪费时间来尝试改善所提供的GPS数据.

Sorry for the downer, but my personal opinion is that you're wasting your time trying to improve the provided GPS data.

从好的方面来说，您的原始GPS数据已经非常好！使用它并感到高兴. :)

On the upside, your raw GPS data is already very good! Use it and be happy. :)

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