Add RST documentation

src/fswAlgorithms/opticalNavigation/positionODuKF/positionODuKF.rst

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+Executive Summary
+-----------------
+
+This module filters position measurements that have been processed from planet images in order to
+estimate spacecraft relative position to an observed body in the inertial frame.
+The filter used is a square root unscented Kalman filter, and the images are first processed by image processing
+and a measurement model in order to produce this filter's measurements.
+
+The module
+:download:`PDF Description </../../src/fswAlgorithms/opticalNavigation/relativeODuKF/_Documentation/inertialUKF_DesignBasis.pdf>`
+contains further information on this module's mathematical framework.
+
+Message Connection Descriptions
+-------------------------------
+The following table lists all the module input and output messages.  The module msg connection is set by the
+user from python.  The msg type contains a link to the message structure definition, while the description
+provides information on what this message is used for.
+
+.. list-table:: Module I/O Messages
+    :widths: 25 25 50
+    :header-rows: 1
+
+    * - Msg Variable Name
+      - Msg Type
+      - Description
+    * - navTransOutMsg
+      - :ref:`NavTransMsgPayload`
+      - navigation translation output message
+    * - opNavFilterMsg
+      - :ref:`OpNavSUKFMsgPayload`
+      - output filter data message containing states and covariances
+    * - cameraPosMsg
+      - :ref:`CameraLocalizationMsgPayload.h`
+      - opnav input message containing the position vector towards the target
+
+Module models
+-------------------------------
+The measurement model for the filter is functionally contained in the cameraTriangulation
+module. The message read in therefore contains the predicted measurement:
+
+.. math::
+
+    H[X] = X[0:3] = \mathbf{r}
+
+The dynamics modules used are point mass, single body gravity, propagated with and RK4
+integrator
+
+.. math::
+
+    F[X] = \dot{X} = - \frac{\mu}{| X[0:3] |^3}X[0:3] = - \frac{\mu}{r^3}\mathbf{r}
+
+where :math:`r` is the position of the spacecraft center of masss relative to the central body
+of gravitational parameter :math:`\mu`.
+
+
+Module assumptions and limitations
+-------------------------------
+
+The module inherits all assumptions made while implementing a Kalman filter:
+    • Observability considerations
+    • Gaussian covariances
+    • Linearity limits
+    • and more
+
+Otherwise, the limitations are governed by the measurement model and dynamics models relative
+to the required performance.
+
+User Guide
+----------
+This section is to outline the steps needed to setup a positionODSRuKF converter in Python.
+
+#. Import the module::
+
+    from Basilisk.fswAlgorithms import positionODSRuKF
+
+#. Create an instantiation of converter class::
+
+    positionOD = positionODuKF.PositionODuKF()
+
+#. Setup SRuKF general parameters::
+
+    positionOD.alpha = 0.02
+    positionOD.beta = 2.0
+
+#. Setup SRuKF measurement parameters, measurement noise Standard Deviation is given in meters::
+
+    positionOD.muCentral = 3000*1E9
+    positionOD.measNoiseScaling = 1
+    positionOD.measNoiseSD = 100 #m
+
+#. Setup initial state and covariances::
+
+    positionOD.stateInitial = [[1000.*1e3], [0], [0], [0.], [-1.*1e3], [0.]]
+    positionOD.covarInitial =[ [10., 0., 0., 0., 0., 0.],
+                             [0., 10., 0., 0., 0., 0.],
+                             [0., 0., 10., 0., 0., 0.],
+                             [0., 0., 0., 0.01, 0., 0.],
+                             [0., 0., 0., 0., 0.01, 0.],
+                             [0., 0., 0., 0., 0., 0.01]]
+
+#. Setup process noise with units of meters and meters/s::
+
+    sigmaPos = 1E2
+    sigmaVel = 1
+    positionOD.processNoise = [[sigmaPos, 0., 0., 0., 0., 0.],
+                      [0., sigmaPos, 0., 0., 0., 0.],
+                      [0., 0., sigmaPos, 0., 0., 0.],
+                      [0., 0., 0., sigmaVel, 0., 0.],
+                      [0., 0., 0., 0., sigmaVel, 0.],
+                      [0., 0., 0., 0., 0., sigmaVel]]
+
+#. Subscribe to the messages, primarily the measurement message::
+
+    positionOD.opNavHeadingMsg.subscribeTo(cameraTriangulation.cameraLocalizationOutMsg)
+