Network-Centric Warfare (NCW) technology is currently being investigated to enhance the military’s effectiveness in the battlespace by providing the warfighter the necessary information to take proper decisions and win wars. One of the main battlespace requirements is surveillance, especially in today’s guerilla warfare theaters, such as the littoral and urban zones. NCW requires warfighters to be networked, self-organizing, spectrally undetectable, and having precise information about hostile targets in their vicinity. Towards this end, we are developing the concept of Netted Wireless Random Noise Radars, which is presented in this paper. The low probability-of-detection (LPD) and low probability-of-intercept (LPI) properties of random noise radars are well-known. Such radar sensors form a self-organizing network-centric architecture, using a deterministically fragmented spectrum to avoid spectral fratricide. The central concept is to use notch filtering to fragment parts of the band-limited non-coherent random noise waveform spectrum, and use these intermediate bandwidths for network communication (target tracking and track fusion) among the wireless sensors. For target detection and ranging, these sensors transmit random noise waveforms combined with continuous signals carrying digital data. As seen by the hostile target, the transmitted waveform appears random and noise-like. However, for the friendly sensors of this system, the noise-like signal contains camouflaged information. The advantages being envisioned with such a system are lower probability of detection due to noise-like transmissions, mobility to sensors due to the self-organizing capability, spectral efficiency due to fragmentation of spectrum, and better immunity to coherent interference due to the use of non-coherent signal waveforms.