The development of satellite swarm technology offers new possibilities for space studies and comes with new challenges. Among them is the need of knowledge on the swarm topology and attitude, especially in the context of space-borne radio interferometry. This paper presents an algorithm that recovers the absolute swarm attitude autonomously. This algorithm uses the imaging capability of a low frequency radio interferometer that acts as a star-tracker using the main radio sources in the sky. The Lost-In-Space (LIS) mode is presented in this paper. This algorithm is studied through numerical simulations. This concept is applied here to the kilometric wavelength spectral range (30 kHz – 1 MHz) but the technique can be extended to higher frequencies. Images are reconstructed using an iterative Discrete Fourier Transform (DFT) at two frequencies and using source subtractions. Pattern-matching is performed with a voting system implemented on geometrical parameters defined by triangles of sources. The radio sky in the working band is modeled by extrapolating down observation of the sky at 50 MHz. The modeled interferometer corresponds to the NOIRE (Nanosatellite pour un Observatoire Interferométrique Radio dans l’Espace) concept study. The accuracy on the recovered swarm attitude is measured for different levels of noise in the interferometric visibilities. The simulation shows that, the suggested algorithm can achieve an attitude knowledge error lower than 1 arcmin for a swarm scale of 100 km. The requirements in terms of memory and computation capability are discussed as well as the limitations of the technique and the simulation.