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Network-enabled electronic warfare (NEW) is the development of modeling and simulation efforts that explore the advantages and limitations of NEW concepts. The advantages of linking multiple electronic support measures (ESM) and electronic attack (EA) assets to achieve improved capabilities across a networked battle force have yet to be quantified. In this paper, we utilize radar sensors as ESM and EA assets to demonstrate the advantages of NEW in collaborative automatic target recognition (CATR). Signal (waveform) design for radar sensor networks (RSN) in NEW is studied theoretically. The conditions for waveform coexistence and the interferences among waveforms in RSN are analyzed. We apply the NEW to CATR via waveform diversity combining and propose maximum-likelihood (ML)-ATR algorithms for nonfluctuating targets as well as fluctuating targets. Simulation results indicate that our NEW-CATR performs much better than the single sensor-based ATR algorithm for nonfluctuating and fluctuating targets.