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)

댓글 수: 2

bio lim
bio lim 2015년 7월 15일
You need to give us more information. What are you observing?
AbelM Kusemererwa
AbelM Kusemererwa 2015년 7월 15일
The attached file is the deltas for GPS measurement

댓글을 달려면 로그인하십시오.

답변 (1개)

Star Strider
Star Strider 2015년 7월 15일

2 개 추천

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.

댓글 수: 2

AbelM Kusemererwa
AbelM Kusemererwa 2015년 7월 15일
They are root mean square error(rmse) of plan position. With your explanation can you please add figure to it to make it clearer?
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')

댓글을 달려면 로그인하십시오.

카테고리

도움말 센터File Exchange에서 Logical에 대해 자세히 알아보기

제품

태그

질문:

2015년 7월 15일

댓글:

2015년 7월 15일

Community Treasure Hunt

Find the treasures in MATLAB Central and discover how the community can help you!

Start Hunting!

Translated by