High-Performance Interference Filters Improve LIDAR Signal-to-Noise Ratio

Oct. 1, 2019
High-performance ultra-narrowband interference filters isolate LIDAR return signals while preventing extraneous light from reaching the detector. Learn which characteristics of these filters are most important for the performance of LIDAR sensors.
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When specified and designed with the specific LIDAR application, sensor type, and platform in mind, ultra-narrowband LIDAR interference filters can optimize signal-to-noise and improve sensor performance.

LIDAR Basics:

LIDAR (Light Detection and Ranging) is a versatile active remote sensing technique that is used in Earth and atmospheric sciences, autonomous vehicles, urban planning, and many other applications. There are many different types of LIDAR sensors, from laser altimeters to Raman LIDAR systems, all with different filtering requirements.

Laser altimeters and other LIDAR sensors scan a pulsed laser across the environment and determine the return time of the reflected signals by calculating the precise position and orientation of the sensor as the signals are emitted and received. To accomplish this, a LIDAR system requires 5 basic components: a laser, either a mechanical or software based scanning system, a receiver or photodetector, a GPS unit, and a high-precision clock. Aerial LIDAR systems also require an inertial measurement unit (IMU) to determine orientation.

The basic equation used to determine the distance between the object and the sensor is:

Where R is the range in meters, c is the speed of light, na is the index of refraction of air, t is the time when the signal returns, and tp is the time when the pulse is emitted.

If a single LIDAR pulse only encounters one object, such as bare ground, the result will be a single corresponding return signal. However, multiple objects such as such as tree branches and shrubs can be encountered before the signal reaches the ground, resulting in multiple reflected signals. Depending on the associated software, LIDAR systems will either record these returns as discrete points, or will display the data as a waveform showing each return as a function of time (Figure 1). The result is a data point cloud that can be used to create high-resolution digital elevation models (DEMs) or 3D images of features in the surrounding environment.

Figure 1: Diagram illustrating the difference between single and multiple return signals from an aerial laser altimeter.

Filtering Technologies:

LIDAR return signals must be isolated using a filtering technology that preserves signal intensity, while, in many cases, simultaneously preventing sunlight and other extraneous light from reaching the detector. Depending on the specific application and sensor type, options can include interference filters, Fabry-Pérot interferometers, Fabry-Pérot etalons, spectrometers, atomic line filters, and filtering algorithms. LIDAR systems requiring a high level of precision generally include a combination of two or more of these filtering techniques.

Although return signals can be isolated using a variety of different filtering technologies, most LIDAR systems are manufactured using thin-film interference filters because of their inherent durability and lack of a need for maintenance or calibration. This is an important consideration because many LIDAR sensors are mounted to satellites, airplanes, UAVs, autonomous vehicles, and other platforms that require the sensor to function under harsh environmental conditions with little to no maintenance.

LIDAR Filters:

Thin-film interference filters are made by depositing alternating layers of materials with contrasting indices of refraction onto a substrate. As light makes its way through the filter, part of the light reflects at each layer, resulting in internal interference. Depending on the thicknesses and configuration of the layers, the net result is that certain wavelengths of light are transmitted through the filter, while others are either absorbed by it or reflected off of it.

Because of the precise nature of LIDAR return signals, most LIDAR filters are ultra-narrowband interference filters. These filters must be able to achieve high transmission over an ultra-narrow bandwidth in order to isolate return signals, and deep out-of-band blocking over a large wavelength range to attenuate extraneous light (Figure 2).

Figure 2: A narrowband LIDAR interference filter.

These filters can be designed with bandwidths as narrow as 0.1 nm without sacrificing transmission, which is typically greater than 90%. The basic design relies on Fabry-Pérot resonant cavities. When a single cavity is used in the design, the result is a filter with a peaked spectral shape. However, as more cavities are added, the passband exhibits a flat top, steeper edges, and greater out-of-band attenuation. Multi-cavity designs therefore allow for more precise transmission of the target signal and greater LIDAR signal-to-noise ratios.

LIDAR systems also require that the filters' thin-film coating must be as uniform as possible. When uniformity is not controlled, the thin-film layer thicknesses vary across the surface of the filter, resulting in a location-dependent wavelength shift of the filter spectrum across the clear aperture. If a filter with uncontrolled uniformity is integrated into a LIDAR system, a large number of LIDAR return signals will end up being blocked by the filter and will not reach the detector. Fortunately, a uniformity-controlled thin-film coating will ensure that target signals will not be blocked by the filter (Figure 3).

Figure 3: A 72 mm diameter uniformity-controlled LIDAR interference filter with < 0.035% variation in center wavelength over the clear aperture.

In addition, LIDAR filters must also be designed with the sensor platform and environmental conditions in mind. Aerial and ground based LIDAR systems operate at temperatures that can range from -40°C to +105°C, while satellite LIDAR operating ranges depend on the orbit and thermal control system of the satellite. Therefore, any interference filters integrated into systems that operate at extreme temperatures should be designed to minimize temperature-dependent wavelength shift.

Interference Filters for Specific LIDAR Applications:

There are many different types of LIDAR sensors, all with differing application-specific filter requirements that must be taken into account in order to maximize signal-to-noise.

Laser altimeters typically require interference filters to be narrower than 1.5 nm at full-width half maximum (FHWM), while achieving over 90% transmission at the laser line and greater than OD6 (-60dB or 0.0001% transmission) out-of-band blocking from ~300 – 1300 nm.

Mie and Rayleigh LIDAR instruments are used for air quality monitoring. They are ground based or forward facing aerial systems that detect the elastic Mie or Rayleigh backscatter of aerosols and homonuclear diatomic gases at laser wavelengths of 355nm, 532nm, and 1064nm. Because atmospheric LIDAR systems rely on relatively weak backscatter signals, every effort must be made to maximize the signal-to-noise ratio. For this reason, Mie and Rayleigh LIDAR filters are generally designed with steep edges and greater than OD7 (-70dB or 0.00001% transmission) out-of-band blocking.

Raman LIDAR is another atmospheric LIDAR technique used to isolate and detect the inelastic rotational and vibrational Raman scattering that occurs when molecules of interest are excited by a laser. Raman LIDAR filters must have extremely steep edges so that the Raman signal is transmitted to the detector while the stronger elastic backscatter signals at the laser wavelength are blocked to a level of OD8 (-80 dB or 0.000001% transmission).

Differential Absorption LIDAR (DIAL) units take advantage of the absorption spectra of water vapor and atmospheric gases in order to determine their concentrations. DIAL systems use two different lasers, the first tuned to an on-resonance, or high-absorption, wavelength for the target molecule, and the second is tuned to an off-resonance wavelength. The on and off-resonance wavelengths are generally less than 1 nm apart, which allows researchers to assume that any measured backscatter differences are due to absorption by the species of interest. This allows for a concentration profile to be determined from the backscatter ratio as a function of range.

Because the near and far channels of DIAL systems are very close in wavelength, these systems generally require ultra-narrow interference filters for sunlight attenuation, while Fabry-Pérot etalons are used to separate the channels. The ultra-narrow interference filters commonly multi-cavity designs with a FWHM of less than 0.5 nm and wide-range, out-of-band blocking that is greater than OD6.

Aside from the sensors mentioned above, fluorescence LIDAR, solid state LIDAR systems for autonomous vehicles, and many other LIDAR systems all have specific interference filter requirements. Click here for a more detailed discussion on application-specific LIDAR interference filter requirements and to learn more about interference filter design.

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