How to improve accuracy?

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AbelM Kusemererwa 2015-7-15

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评论： Star Strider 2015-7-15

GPS.jpg

Attached is an example of deltas(difference between the observed and the truth). How can I improve by making these deltas or residuals smaller(approach to zero)

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bio lim 2015-7-15

You need to give us more information. What are you observing?

AbelM Kusemererwa 2015-7-15

The attached file is the deltas for GPS measurement

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Answer 1

Star Strider 2015-7-15

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All the values are positive, leading me to believe they are absolute distances from some reference. You likely cannot improve the accuracy of any measurement, but you can reduce the error by averaging the ‘raw’ GPS readings (not the derived distances) over a small window, then deriving the distance and calculating the error. That will likely reduce it. You can never eliminate it entirely.

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AbelM Kusemererwa 2015-7-15

They are root mean square error(rmse) of plan position. With your explanation can you please add figure to it to make it clearer?

Star Strider 2015-7-15

在 MATLAB Online 中打开

I would use a moving-average filter with a short window on each of the (x,y,z) elements in your GPS data.

This code snippet illustrates the idea. You can use either filter (core MATLAB) or filtfilt (Signal Processing Toolbox) to do the moving-average filtering:

L = 100;                                    % Data Record Length
v = 1:L;
xyz = randn(L, 3);                          % Hypothetical GPS Data (Lx3)
N = 5;                                      % Moving Average Filter Length
filt_b = ones(1, N);
filt_a = N;
xyz_avg = filter(filt_b, filt_a, xyz);
xyz_dist = sqrt(sum(xyz.^2, 2));            % Sum Across Rows
xyz_avg_dist = sqrt(sum(xyz_avg.^2, 2));    % Sum Across Rows
figure(1)
plot(v, xyz_dist,  v, xyz_avg_dist)
grid
xlabel('Observation #')
ylabel('Distance From Reference')
legend('Raw Data', 'Moving Average Of Data')