The CRLBs computed for a point target as a function of target radial position or depth are displayed in Figs. 1(b) and 1(c). Figure 1(b) illustrates the CRLBs for target depth, while Fig. 1(c) displays the CRLBs for target . The bounds for target angle as a function of target radial position are not shown; they are essentially uniform for each detector configuration, except in the immediate vicinity of where angle is not uniquely defined. (Because we collect measurements over a full 360 deg, the CRLBs show no dependency on target angle, so results as a function of target angle are also not shown for brevity.) Since the bounds are reported as standard deviations, lower values indicate better (i.e., more accurate) performance. We see that as expected, all detector configurations perform better with a shallow target than a more deeply embedded one. From these plots, with respect to estimating target depth, we expect the nine-detector configuration that goes out to (det9_45) to perform about as well as the 37-detector configuration (det37), which has more than four times the number of measurements. Surprisingly, the other nine-detector configuration (det9_90) is similar in performance to the three-detector configuration (det3). With respect to estimating target , performance as a function of depth is rather stable, although the configurations with detectors at (det9_90 and det37) seem to suffer when the target is deeper. We note that the trends observed in these plots are in part a direct result of the way that we have chosen to limit the maximum SNR for each configuration, as detectors closer to 0 deg in configurations with elements at , see SNRs that are lower than than what they measure in the or configurations. If we did not equalize the the maximum SNR across configurations, those with detectors at would have the advantage, since being closer to the source, these detectors would measure higher SNRs. In general, however, given our manner of capping SNR per configuration, those detector arrangements without elements that go out to appear to have a distinct performance advantage.