Autonomous Wide Aperture Cluster for Surveillance: Adaptive and Collaborative Signal Processing

AUTONOMOUS WIDE APERTURE CLUSTER FOR SURVEILLANCE: ADAPTIVE AND COLLABORATIVE SIGNAL PROCESSING

Jeffrey L. Krolik

Department of Electrical and Computer Engineering Duke University, Box 90291, Durham, NC 27708 Ph: (919) 660-5274, Fax: (919) 660-5293, email: [email protected] ONR award number: N000140510411 http://www.ee.duke.edu/~jk/index.html

OBJECTIVES

The goal of this project is to develop signal processing algorithms and analysis for an Autonomous Wide Aperture Cluster for Surveillance (AWACS). Each AWACS will be a local area network (LAN) of dynamically reconfigurable sensor arrays (DRSA's) which collaboratively maintain maximum passive detection performance over a regional surveillance area. Each line array within a LAN will be towed by an autonomous underwater vehicle (AUV) and controlled by an autonomous gateway. The orientations, translations, and separations of the AUV-towed-arrays within a LAN will be continually updated to maximize their collective array gain across prescribed sectors of bearing space as a function of the continually predicted acoustic noise directionality and oceanographic conditions. Duke is responsible for the design and evaluation of the algorithms which will optimally configure the AWACS over shorter time-scales (e.g. hours) as well as other advanced signal and array processing algorithms.

APPROACH

Before considering how each dynamically reconfigurable sensor array (DRSA) operates, consider the limitations of conventional towed line-array performance illustrated by the conventional bearing- time-record (BTR) in Figure 1 from a real 90-meter long 30-element passive uniform linear array (ULA) operating at approximately 250 Hz. Passive sonar target detection is performed using this beamformer output power versus sin-bearing plot (a.k.a. field directionality or spatial spectrum) to identify tracks consistent with target dynamics over time. Note that while source tracks are evident at sin-bearings between 0.5 , towards both endfire directions (i.e. nearer sin-bearings of 1), the BTR is much noisier. This well-known characteristic results from the poorer directivity of line arrays towards end-fire and tow-ship noise, resulting in both poorer resolution and lower array gain. The conventional approach to improving resolution, so critical in highly cluttered littoral environments, is to lengthen the array and/or use adaptive beamforming. For example, the generalized Rayleigh beamwidth, q Rayleigh , for q an N element array with inter-element spacing, d, as a function of look bearing, look , is given by l 1 q Rayleigh @ where l is the acoustic wavelength and f is the elevation angle. Nd cos(qlook )cos( f )

Making the array longer by increasing N helps mitigate this loss as qlook goes towards endfire (i.e.

1 cos(qlook ) 0 ), but exacerbates signal wavefront mismatch due to multipath and wavefront curvature. Moreover, for adaptive beamformers, the number of snapshots, M, available for estimating the adaptive beamformer weights actually decreases with array length and goes as M(l / Nd )2 . In addition to

Figure 1: Bearing Time Record from a 90-foot towed horizontal array [Image: BTR with weak source tracks near broadside and interferers obscuring much of the angles toward the endfire directions] degradation at endfire, line arrays are notoriously hampered by left-right ambiguities. This is a result of the fact that a line array on the x axis cannot distinguish between directional elements at sin(q ) or sin(p- q ) . Although in the relatively uncluttered scenario of Figure 1, this has little impact, in busy littoral areas, it results in weak targets at q being commonly masked by interferences in the “back- beam” at p- q . Conventional approaches for mitigating back-beam interference include using twin- line and planar arrays, although these are typically expensive and difficult to deploy.

Another interpretation of the field directionality measured at a line array, that leads to a powerful approach for improving array gain in interference-dominated scenarios, is as a projection of a 3-D spatial spectrum with wavenumber components, kx, k y , and kz . Consider for simplicity the 2-D wavenumber spectrum illustrated in Figure 2. The acoustic field directionality from 0 to 2p is 2 2 2 portrayed as the color-coded band along a circle corresponding to kx+ k y = (2p l ) . The mainlobes for a set of contiguous beams, m= 1, , M measured by an array oriented along the x-axis are illustrated by the vertical stripe regions. The beam power versus sin-bearing measured at the array is thus the sum (i.e. projection) of the power along the beams. The impairments of a conventional line array can be seen immediately by noting that for this orientation, the target is masked by Interference 1 in the back-beam. Moreover, a further degradation of the field directionality estimate for this orientation occurs due to Interference 2 and 3 being spread in the projected sin-bearing space. This would result in a loss of usable bearing space available to detect targets with conventional

2 beamforming and/or a significant increase in the number of degrees of freedom (and commensurate snapshot support) required to do adaptive nulling.

Figure 2: Fixed array 2-D wavenumber Space Figure 3: Rotated array 2-D wavenumber space [Image: Illustration of beam on target with [Image: Illustration of rotated array with beam on interference in the back-beam] target and separated interferers]

The key idea behind the DRSA concept stems from the realization that the orientations of multiple one-dimensional line arrays can be adaptively selected to optimally sample the two (and even three) dimensional acoustic field. This corresponds to taking different one-dimensional projections of two (or three) dimensional wavenumber space. The advantage of DRSA’s versus conventional towed or fixed arrays is thus that the observed projections of 3-D wavenumber space can be dynamically optimized to maximize array gain for a hypothesized target direction, sector, or the entire isotropic field of view. This idea is illustrated by rotating the array p 4 in the scenario of Figure 2. The resulting beams in the rotated projection in 2-D wavenumber space are shown in Figure 3. Note that by simply changing the orientation of the array, we have not only removed Interference 1 from the target back-beam but also collapsed Interferers 2 and 3 into a single beam which would result in a substantial increase in usable bearing space. By analogy to medical imaging, the idea is like having a CAT scan with optimally chosen scan orientations that depend on the nature of the object being imaged versus being restricted to just one arbitrary orientation.

RESULTS At this early stage in the project, we have mainly performed simulations of a single DRSA which illustrate the dramatic array gain improvement that can be achieved. As an example, consider the simulation scenario shown in Figure 4 consisting of a weak target in the presence of 5 strong interferers. For

comparison purposes, conventional beamforming with a fixed array (in blue) oriented with broadside at zero degrees is compared with the DRSA orientation which provides the maximum average array 3 gain over all bearings. The orientation of the single DRSA (in red) was optimized assuming the interference is in the light blue sector which is an imperfect, but reasonable, model of the true interference locations, whose initial bearings are shown. Besides interference, distant shipping, and tow-vehicle noise has been included in the simulation. The bearing-time-record (BTR) of a conventionally beamformed (CBF), fixed 20-element array at 2l 5spacing is shown in Figure 5. Note

Figure 4: Interferers and target sector Figure 5: Conventional BTR with Fixed ULA [Image: Shows target in back beam of [Image: Shows target completely masked by fixed ULA but not for optimal DRSA] strong interferer after time epoch 150] that the target at bearing 45 degrees is completely masked by interferers in the back-beams. The BTR Figure 6: Bearing Time Record for DRSA Figure 7: Array Gain vs. Time

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[Image: Shows target resolved from interferers] [Image: Shows DRSA improvement over fixed ULSA CBF and ABF] of the optimally oriented DRSA array is shown in Figure 6. Note that the target at 45 degrees is completely unmasked and the apparent interference bearings have been compressed into bearings beyond 150 degrees. The unusable region near 0 degrees in Figure 6 (as well as 90 degrees in Figure 5) represents the tow-ship and two-cable strum components that appear along the endfire 4 directions regardless of array orientation. Figure 7 compares the array gain for the CBF, clairvoyant adaptive beamforming (ABF) with the fixed array, and CBF for the DRSA with the result that the ideally-oriented DRSA ULA offers by far the best array gain, even beating clairvoyant ABF with the fixed ULA. This is due to the inability of the fixed array CBF or ABF to mitigate interference that is in the ambiguous back-beam of the array.

RELATED PROJECTS:

The AWACS project is somewhat related to our passive and active sonar signal processing 6.1 research sponsored by ONR code 321US.

PUBLICATIONS:

The following paper has been published as a result of current FY05 research activities on this new grant:

1. Varadarajan, V. and Krolik, J. "Target detection using dynamically reconfigurable sensor arrays", Proceedings ICASSP '05, IEEE International Conference on Acoustics, Speech, and Signal Processing, Volume 4, 18-23 March 2005 Page(s):iv/1009 - iv/1012.