The Constant Information Radar

Abstract

Abstract:The constant information radar, or CIR, is a tracking radar that modulates target revisit time by maintaining a fixed mutual information measure. For highly dynamic targets that deviate significantly from the path predicted by the tracking motion model, the CIR adjusts by illuminating the target more frequently than it would for well-modeled targets. If SNR is low, the radar delays revisit to the target until the state entropy overcomes noise uncertainty. As a result, we show that the information measure is highly dependent on target entropy and target measurement covariance. A constant information measure maintains a fixed spectral efficiency to support the RF convergence of radar and communications. The result is a radar implementing a novel target scheduling algorithm based on information instead of heuristic or ad hoc methods. The CIR mathematically ensures that spectral use is justified.

Radar Waveform Optimization for Joint Radar Communications Performance

“…It should be noted that the integrals shown in Equations (5) and (6) are evaluated numerically to determine the optimal value for µ and the communications data rate, due to the complexity involved in determining analytical solutions for these integrals.…”

“…The spectral shape of the waveform (set by the parameters chosen by the design method) determines whether the radar performance or the communications performance is maximized, or some weighting therein. The performance of communications is measured by the communications rate R com (bits/s), given by Equations (6), and the performance of estimation is measured by the global estimation rate, R est , (bits/s), given by Equation 7. Given an amount of spectral allocation or bandwidth, forcing the radar spectrum to be more impulse-like (most of the waveform energy is located at frequencies closer to the center of the bandwidth allocation) will reduce the noise spectral density, N int+n ( f ), due to minimal radar residual values (N resi ( f )), thereby maximizing the data rate.…”

“…Refs. [3,[5][6][7] presented performance bounds which were shown to depend on the RMS bandwidth of the radar waveform. In [8], the estimation rate was extended to account for global errors, and an evolutionary optimization algorithm was applied to find the optimal spectral mask that maximizes both radar and communications performance.…”

“…In order to better understand cooperative spectrum sharing between radar and communications systems, Refs. [3,[5][6][7] investigated the fundamental limits on performance for in-band cooperative radar and communications systems and developed system performance bounds. In these works, the performance bounds of a joint radar communications system was found to be dependent on the radar waveform spectral shape or root mean square (RMS) bandwidth.…”

“…In [8], the estimation rate was extended to account for global errors, and an evolutionary optimization algorithm was applied to find the optimal spectral mask that maximizes both radar and communications performance. Several extensions to these performance bounds were presented in [6,10,12]. With the spectral congestion problem rapidly becoming a reality, researchers have searched diverse areas for potential solutions.…”