Alternatives to offline Kalman filtering
If you used a commercial GPS receiver to obtain your tracking data, the raw trilateration data from satellites are already processed &quot;using Kalman filtering (more common) or least-squares (less common) estimation algorithms&quot; (see https://insidegnss-com.exactdn.com/wp-content/uploads/2018/01/marapr13-Solutions.pdf). Pay attention also to the counterintuitive statement that the article proves in the section *No Silver Bullet&quot;: the differences between least-squares and Kalman are surprisingly minor for the generic application in GPS receivers.
With this in mind, additional post-processing is quite unlikely to improve your data set, but instead your data can deteriorate as a result of this post-processing. It seems you cannot denoise your data any better, but you can analyze your route (whether the highway route passes &quot;canyons&quot;, sharp corners or the like) and, knowing the features of your GPS receiver taken from the manufacturer's datasheet, estimate the precision of your tracking data.
The article referenced also gives a partial answer to your highlighted question about an &quot;alternative&quot;.