David W. Illig

Statistical backscatter suppression technique for a wideband hybrid lidar-radar ranging system

A new backscatter suppression technique is applied to a wideband modulation scheme to enhance optical ranging in underwater environments. The statistical digital signal processing (DSP) approach of blind signal separation (BSS) [1-2] is applied to a frequency domain reflectometry (FDR) [3-4] ranging system. Applying BSS to the FDR system allows the backscatter return to be dynamically measured and cancelled out before computing range. Results from simulations and laboratory experiments are presented to demonstrate the combined FDR/BSS approach.

FMCW optical ranging technique in turbid waters

The performance of a frequency-modulated continuous-wave (FMCW) hybrid lidar-radar system will be presented in the context of an underwater optical ranging application. In adapting this technique from the radar community, a laser is intensity-modulated with a linear frequency ramp. A custom wideband laser source modulated by a new wideband digital synthesizer board is used to transmit an 800 MHz wide chirp into the underwater channel. The transmitted signal is mixed with a reference copy to obtain a “beat” signal representing the distance to the desired object. The expected form of the return signal is derived for turbid waters, a highly scattering environment, indicating that FMCW can detect both the desired object and the volumetric center of the backscatter “clutter” signal. This result is verified using both laboratory experiments and a realistic simulation model of the underwater optical channel. Ranging performance is explored as a function of both object position and water turbidity. Experimental and simulated results are in good agreement and performance out to ten attenuation lengths is reported, equivalent to 100 meters in open ocean or 5 meters in a turbid harbor condition.

Optical ranging techniques in turbid waters

In this paper simulation and experimental results are presented for two hybrid lidar-radar modulation techniques for underwater laser ranging. Both approaches use a combination of multi-frequency and single frequency modulation with the goal of simultaneously providing good range accuracy, unambiguous range, and backscatter suppression. The first approach uses a combination of dual and single frequency modulation. The performance is explored as a function of increasing average frequency while keeping the difference frequency of the dual tones constant. The second approach uses a combination of a stepped multi-tone modulation called frequency domain reflectometry (FDR) and single frequency modulation. The FDR technique is shown to allow simultaneous detection of the range of both the volumetric center of the backscattered “clutter” signal and the desired object. Experimental and simulated results are in good agreement for both techniques and performance out to ten attenuations lengths is reported.

Independent component analysis for underwater lidar clutter rejection

This work demonstrates a new statistical approach towards backscatter “clutter” rejection for continuous-wave underwater lidar systems: independent component analysis. Independent component analysis is a statistical signal processing technique which can separate a return of interest from clutter in a statistical domain. After highlighting the statistical processing concepts, we demonstrate that underwater lidar target and backscatter returns have very different distributions, facilitating their separation in a statistical domain. Example profiles are provided showing the results of this separation, and ranging experiment results are presented. In the ranging experiment, performance is compared to a more conventional frequency-domain filtering approach. Target tracking is maintained to 14.5 attenuation lengths in the laboratory test tank environment, a 2.5 attenuation length improvement over the baseline.

Time of flight measurements for optically illuminated underwater targets using Compressive Sampling and Sparse reconstruction

Compressive Sampling and Sparse reconstruction theory is applied to a linearly frequency modulated continuous wave hybrid lidar/radar system. The goal is to show that high resolution time of flight measurements to underwater targets can be obtained utilizing far fewer samples than dictated by Nyquist sampling theorems. Traditional mixing/down-conversion and matched filter signal processing methods are reviewed and compared to the Compressive Sampling and Sparse Reconstruction methods. Simulated evidence is provided to show the possible sampling rate reductions, and experiments are used to observe the effects that turbid underwater environments have on recovery. Results show that by using compressive sensing theory and sparse reconstruction, it is possible to achieve significant sample rate reduction while maintaining centimeter range resolution.

Image processing technique for an underwater modulated pulse laser imaging system

This work presents a processing technique for enhancing images collected by an underwater modulated pulse laser imaging system. Laser-based sensors offer high-resolution and high-accuracy ranging in the underwater environment. However, these capabilities can be degraded in turbid waters due to scattering. This work presents experimental results demonstrating an image processing technique that reduces the effects of both backscatter and forward scatter. Without the use of gating, filtering, or a priori information, the processing technique can generate useful imagery to 6.9 attenuation lengths in a controlled laboratory environment.

Energy-Harvesting Low-Power Devices in Cyber-Physical Systems

Cyber-physical systems (CPSs) widely use sensors and actors for monitoring and controlling the physical elements of the CPS. Reliability and lifetime of those sensors and actors play an important role in the reliability and availability of the whole system. The limited battery capacity of the sensors and actors emerge as a significant challenge in hyper-connected CPSs, mostly because intense communications in a limited physical space drain batteries faster than conventional sensor applications. Energy conservation and energy harvesting approaches increase the lifetime of sensors. However, traditional energy harvesting techniques do not serve as deterministic sources of energy due to their intermittent availability. Recently, low-power sensors with radio frequency (RF) energy harvesting capability have become commercially available. In this chapter, we motivate the use of RF-powered sensors in CPSs. The chapter introduces results from RF energy harvesting in sensor networks and in heterogenous wireless networks. In addition, the chapter discusses and presents some preliminary results on relayed energy transfer.

Blind signal separation for underwater lidar applications

Blind signal separation (BSS) is demonstrated to improve signal-to-interference ratio (SIR) in underwater light detection and ranging (lidar) applications. Lidar systems are used for high-resolution ranging and imaging underwater. A difficult problem in this area is detecting the return from an object of interest in the presence of a strong “clutter” return caused by backscattering in low visibility water environments. The principal component analysis form of BSS is applied to separate the return into multiple subspaces, with the backscatter subspace suppressed to improve detection capability. Simulations are performed using an underwater optical channel model to simulate a challenging harbor-like environment. We show that the processing gain from BSS is increased when the correlation energy between observations is increased, for example by using closely spaced observations. The SIR gain of BSS is explored as a function of frequency, achieving substantial gain independently of carrier frequency. This result has important implications on the design of lidar systems, suggesting that BSS can be combined with low-cost, low-frequency components to achieve performance similar to systems using high-frequency components.

Backscatter suppression via blind signal separation for a 532 nm underwater chaotic lidar rangefinder

Blind signal separation is applied to suppress backscatter for a 532 nm chaotic lidar underwater rangefinder. When operating in turbid waters, chaotic lidar returns contain information for both submerged objects and an optical backscatter “clutter” component. The statistical digital signal processing technique of blind signal separation (BSS) is applied to dynamically measure and cancel out the backscatter component before computing range to the desired object. Results from simulations and laboratory experiments are presented to demonstrate the combined chaotic/BSS approach. The chaotic/BSS approach extends operating range by almost 40% and achieves centimeter-order range accuracy. Receiver operating curves are simulated for the chaotic/BSS approach, which show convergence towards the ideal classifier in several conditions of interest.

A wideband noise-like transmitter approach for underwater lidar using diode lasers and passive fiber optic processors

A new wideband noise-like transmitter approach is presented for high resolution underwater lidar sensing. The transmitter approach is based on small-footprint, low-cost components, using low coherence time laser diodes and passive fiber processors to generate wideband noise-like intensity modulation signals in the blue-green optical spectrum. Prototype transmitters are demonstrated using both blue and green laser diodes with passive fiber interferometer structures. Laboratory water tank experiments using a two-diode 516/518 nm prototype transmitter show centimeter range error and 30 cm range resolution while detecting a submerged gray target in up to ten attenuation lengths of turbid water. Experimentally observed challenges for target rangefinding are discussed, including shot noise, backscatter returns, and self-clutter. Strategies are proposed to mitigate these challenges and enhance performance when operating at long standoff distances in turbid waters.