Distance sampling is a popular statistical method to estimate the density of wild animal populations. Conventional distance sampling represents animals as fixed points in space that are detected with an unknown probability that depends on the distance between the observer and the animal. Animal movement, responsive or non-responsive to the observer, can cause substantial bias in density estimation. Methods to correct for responsive animal movement exist, but none account for non-responsive movement independent of the observer. Here, an explicit animal movement model is incorporated into distance sampling, combining distance sampling survey data with independently obtained animal telemetry data.A detection probability that depends on the entire unobserved path the animal travels is derived in continuous space-time. The intractable integration overall possible animal paths is approximated by a hidden Markov model. A simulation study shows the method to be negligibly biased (less than 5%) in scenarios where conventional distance sampling overestimates abundance by up to 100%.The method is applied to a line transect survey of spotted dolphins (Stenella attenuata attenuata) in the eastern tropical Pacific.