The successful realization of next generation radar systems have high performance demands on the signal processing chain. Among these are advanced Active Electronically Scanned Array (AESA) radars in which complex calculations are to be performed on huge sets of data in real-time. Manycore architectures are designed to provide flexibility and high performance essential for such streaming applications. This paper deals with the implementation of compute-intensive parts of AESA radar signal processing chain in a high-level dataflow language; CAL. We evaluate the approach by targeting a commercial manycore architecture, Epiphany, and present our findings in terms of performance and productivity gains achieved in this case study. The comparison of the performance results with the reference sequential implementations executing on a state-of-the-art embedded processor show that we are able to achieve a speedup of 1.6x to 4.4x by using only 10 cores of Epiphany. © Springer Science+Business Media New York 2015