so i got three variables, my location, my target location and the compass heading.
how can i calculate where the target location should be represented on a virtual radar?
i guess i first must calculate the distance between the two gps points and the angle of them relative to north or so. and then there should be a formula with sin or cos to place that point on a coordinate system...?
ps: in javascript...
Start with simpler problems.
In 2D, try converting back and forth between cartesian and polar coordinates. References are available.
Do the same, but for the polar coordinates use an observer who measures angles from some ray that is not in the X direction.
The same, but using an origin for the polar coordinates that is not at {x=0,y=0}.
In 3D, go back and forth between cartesian and spherical coordinates.
Again, with spherical coordinates in an arbitrary orientation, using an arbitrary origin.
Now convert from GPS coordinates (which are spherical) to cartesian, then to radar-centered spherical.
Related
I have 3 points in Cartesian coordinate system. I know the inter distance between the points. I also know the distance of the points from the origin. Is it possible to know the coordinates of the points?
This isn’t enough information to determine the locations of the points.
Imagine that you have found one possible location for those three points. Take the points and rotate each of them around the origin by the same angle θ. This preserves all the distances between the points and between the points and the origin, but gives a different solution to the original set of constraints.
We have static point at lat1,lon1 and moving point with lat2,lon2 and direction D. Direction is an integer that comes with GPS coordinates.
Two points distance is a few kilometers, so we can suppose that earth is flat.
How can we check if second point moving in direction of first point or not? And if not how to calculate "right" direction for second point.
P.S. I will be also grateful for any good documentation about how direction from PGS coordinate pack works.
I need to project a 3D object onto a sphere's surface (uhm.. like casting a shadow).
AFAIR this should be possible with a projection matrix.
If the "shadow receiver" was a plane, then my projection matrix would be a 3D to 2D-plane projection, but my receiver in this case is a 3D spherical surface.
So given sphere1(centerpoint,radius),sphere2(othercenter,otherradius) and an eyepoint how can I compute a matrix that projects all points from sphere2 onto sphere1 (like casting a shadow).
Do you mean that given a vertex v you want the following projection:
v'= centerpoint + (v - centerpoint) * (radius / |v - centerpoint|)
This is not possible with a projection matrix. You could easily do it in a shader though.
Matrixes are commonly used to represent linear operations, like projection onto a plane.
In your case, the resulting vertices aren't deduced from input using a linear function, so this projection is not possible using a matrix.
If the sphere1 is sphere((0,0,0),1), that is, the sphere of radius 1 centered at the origin, then you're in effect asking for a way to convert any location (x,y,z) in 3D to a corresponding location (x', y', z') on the unit sphere. This is equivalent to vector renormalization: (x',y',z') = (x,y,z)/sqrt(x^2+y^2+z^2).
If sphere1 is not the unit sphere, but is say sphere((a,b,c),R) you can do mostly the same thing:
(x',y',z') = R*(x-a,y-b,z-c) / sqrt((x-a)^2+(y-b)^2+(z-c)^2) + (a,b,c). This is equivalent to changing coordinates so the first sphere is the unit sphere, solving the problem, then changing coordinates back.
As people have pointed out, these functions are nonlinear, so the projection cannot be called a "matrix." But if you prefer for some reason to start with a projection matrix, you could project first from 3D to a plane, then from a plane to the sphere. I'm not sure if that would be any better though.
Finally, let me point out that linear maps don't produce division-by-zero errors, but if you look closely at the formulas above, you'll see that this map can. Geometrically, that's because it's hard to project the center point of a sphere to its boundary.
I'm trying to figure out some calculations using arcs in 3d space but am a bit lost. Lets say that I want to animate an arc in 3d space to connect 2 x,y,z coordinates (both coordinates have a z value of 0, and are just points on a plane). I'm controlling the arc by sending it a starting x,y,z position, a rotation, a velocity, and a gravity value. If I know both the x,y,z coordinates that need to be connected, is there a way to calculate what the necessary rotation, velocity, and gravity values to connect it from the starting x,y,z coordinate to the ending one?
Thanks.
EDIT: Thanks tom10. To clarify, I'm making "arcs" by creating a parabola with particles. I'm trying to figure out how to ( by starting a parabola formed by a series particles with an beginning x,y,z,velocity,rotation,and gravity) determine where it will in end(the last x,y,z coordinates). So if it if these are the two coordinates that need to be connected:
x1=240;
y1=140;
z1=0;
x2=300;
y2=200;
z2=0;
how can the rotation, velocity, and gravity of this parabola be calculated using only these variables start the formation of the parabola:
x1=240;
y1=140;
z1=0;
rotation;
velocity;
gravity;
I am trying to keep the angle a constant value.
This link describes the ballistic trajectory to "hit a target at range x and altitude y when fired from (0,0) and with initial velocity v the required angle(s) of launch θ", which is what you want, right? To get your variables into the right form, set the rotation angle (in the x-y plane) so you're pointing in the right direction, that is atan(y/x), and from then on out, to match the usual terminology for 2D problem, rewrite your z to y, and the horizontal distance to the target (which is sqrt(xx + yy)) as x, and then you can directly use the formula in link.
Do the same as you'd do in 2D. You just have to convert your figures to an affine space by rotating the axis, so one of them becomes zero; then solve and undo the rotation.
It's been a while since my math in university, and now I've come to need it like I never thought i would.
So, this is what I want to achieve:
Having a set of 3D points (geographical points, latitude and longitude, altitude doesn't matter), I want to display them on a screen, considering the direction I want to take into account.
This is going to be used along with a camera and a compass , so when I point the camera to the North, I want to display on my computer the points that the camera should "see". It's a kind of Augmented Reality.
Basically what (i think) i need is a way of transforming the 3D points viewed from above (like viewing the points on google maps) into a set of 3d Points viewed from a side.
The conversion of Latitude and longitude to 3-D cartesian (x,y,z) coordinates can be accomplished with the following (Java) code snippet. Hopefully it's easily converted to your language of choice. lat and lng are initially the latitude and longitude in degrees:
lat*=Math.PI/180.0;
lng*=Math.PI/180.0;
z=Math.sin(-lat);
x=Math.cos(lat)*Math.sin(-lng);
y=Math.cos(lat)*Math.cos(-lng);
The vector (x,y,z) will always lie on a sphere of radius 1 (i.e. the Earth's radius has been scaled to 1).
From there, a 3D perspective projection is required to convert the (x,y,z) into (X,Y) screen coordinates, given a camera position and angle. See, for example, http://en.wikipedia.org/wiki/3D_projection
It really depends on the degree of precision you require. If you're working on a high-precision, close-in view of points anywhere on the globe you will need to take the ellipsoidal shape of the earth into account. This is usually done using an algorithm similar to the one descibed here, on page 38 under 'Conversion between Geographical and Cartesian Coordinates':
http://www.icsm.gov.au/gda/gdatm/gdav2.3.pdf
If you don't need high precision the techniques mentioned above work just fine.
could anyone explain me exactly what these params mean ?
I've tried and the results where very weird so i guess i am missunderstanding some of the params for the perspective projection
* {a}_{x,y,z} - the point in 3D space that is to be projected.
* {c}_{x,y,z} - the location of the camera.
* {\theta}_{x,y,z} - The rotation of the camera. When {c}_{x,y,z}=<0,0,0>, and {\theta}_{x,y,z}=<0,0,0>, the 3D vector <1,2,0> is projected to the 2D vector <1,2>.
* {e}_{x,y,z} - the viewer's position relative to the display surface. [1]
Well, you'll want some 3D vector arithmetic to move your origin, and probably some quaternion-based rotation functions to rotate the vectors to match your direction. There are any number of good tutorials on using quaternions to rotate 3D vectors (since they're used a lot for rendering and such), and the 3D vector stuff is pretty simple if you can remember how vectors are represented.
well, just a pice ov advice, you can plot this points into a 3d space (you can do easily this using openGL).
You have to transforrm the lat/long into another system for example polar or cartesian.
So starting from lat/longyou put the origin of your space into the center of the heart, than you have to transform your data in cartesian coord:
z= R * sin(long)
x= R * cos(long) * sin(lat)
y= R * cos(long) * cos(lat)
R is the radius of the world, you can put it at 1 if you need only to cath the direction between yoour point of view anthe points you need "to see"
than put the Virtual camera in a point of the space you've created, and link data from your real camera (simply a vector) to the data of the virtual one.
The next stemp to gain what you want to do is to try to plot timages for your camera overlapped with your "virtual space", definitevly you should have a real camera that is a control to move the virtual one in a virtual space.