In this paper, we study topologies of sensor networks deployed for tracking multiple targets withBlind Source Separation (BSS), a statistical signal processing technique widely used to recover individual signals from mixtures of signals. BSS-based tracking algorithms are proven to be effective in tracking multiple indistinguishable targets. The topology of a wireless sensor network deployed for tracking with BSS-based algorithms is critical to tracking performance: (a) The topology affects separation performance. (b) The topology determines accuracy and precision of estimation on the paths taken by targets. We propose cluster topologies for BSS-based tracking algorithms. Guidelines on parameter selection for proposed topologies are given in this paper. We evaluate proposed cluster topologies with extensive experiments. Our empirical experiments also show that BSS-based tracking algorithm can achieve comparable tracking performance in comparison with algorithms assuming single target or distinguishable targets.