Fix typos with cspell (#6972)

wpimath/src/main/native/include/frc/estimator/KalmanFilterLatencyCompensator.h

@@ -59,7 +59,7 @@ class KalmanFilterLatencyCompensator {
    * @param observer  The observer.
    * @param u         The input at the timestamp.
    * @param localY    The local output at the timestamp
-   * @param timestamp The timesnap of the state.
+   * @param timestamp The timestamp of the state.
    */
   void AddObserverState(const KalmanFilterType& observer, Vectord<Inputs> u,
                         Vectord<Outputs> localY, units::second_t timestamp) {

wpimath/src/main/native/include/frc/estimator/MerweScaledSigmaPoints.h

@@ -18,7 +18,7 @@ namespace frc {
  * version seen in most publications. Unless you know better, this should be
  * your default choice.
  *
- * [1] R. Van der Merwe "Sigma-Point Kalman Filters for Probabilitic
+ * [1] R. Van der Merwe "Sigma-Point Kalman Filters for Probabilistic
  *     Inference in Dynamic State-Space Models" (Doctoral dissertation)
  *
  * @tparam States The dimensionality of the state. 2 * States + 1 weights will

wpimath/src/main/native/include/frc/estimator/SteadyStateKalmanFilter.h

@@ -48,7 +48,7 @@ class SteadyStateKalmanFilter {
   using OutputArray = wpi::array<double, Outputs>;
 
   /**
-   * Constructs a staeady-state Kalman filter with the given plant.
+   * Constructs a steady-state Kalman filter with the given plant.
    *
    * See
    * https://docs.wpilib.org/en/stable/docs/software/advanced-controls/state-space/state-space-observers.html#process-and-measurement-noise-covariance-matrices

wpimath/src/main/native/include/frc/estimator/UnscentedTransform.h

@@ -30,7 +30,7 @@ namespace frc {
  *                     vectors using a given set of weights.
  * @param residualFunc A function that computes the residual of two state
  *                     vectors (i.e. it subtracts them.)
- * @param squareRootR  Square-root of the noise covaraince of the sigma points.
+ * @param squareRootR  Square-root of the noise covariance of the sigma points.
  *
  * @return Tuple of x, mean of sigma points; S, square-root covariance of
  * sigmas.