A fundamental problem in sensor array signal processing is to separate and retrieve all independent co-channel signals that arrive at the antenna array. Such problems arise in smart antenna applications for mobile wireless communication, such as interference reduction and in- cell frequency reuse. In a mobile environment, the presence of large delay multipath makes the array manifold poorly defined, and spatial model methods are not applicable. However in case the signals have a constant modulus property (as in FDMA/FM systems like AMPS or TACS), iterative algorithms such as Godard and CMA have been used to retrieve the signals. Because of a non-convex optimization criterion, these algorithms suffer from local minima and random convergence behavior, with no satisfactory remedy known as yet. In this paper, we present an algorithm to compute the exact solution to the underlying constant modulus (CM) factorization problem. With this new approach, it is possible to detect the number of CM signals present at the array, and to retrieve all of them exactly, rejecting other, non-CM signals. Only a modest amount of samples are required. The algorithm is robust in the presence of noise, and is tested on real data, collected from an experimental set-up.