Individual focal plane size, yield, and quality continue to improve, as does the technology required to combine these into
large tiled formats. As a result, next-generation pushbroom imagers are replacing traditional scanning technologies in
remote sensing applications.
Pushbroom architecture has inherently better radiometric sensitivity and significantly reduced payload mass, power, and
volume than previous generation scanning technologies. However, the architecture creates challenges achieving the
required radiometric accuracy performance. Achieving good radiometric accuracy, including image spectral and spatial
uniformity, requires creative optical design, high quality focal planes and filters, careful consideration of on-board
calibration sources, and state-of-the-art ground test facilities.
Ball Aerospace built the Landsat Data Continuity Mission (LDCM) next-generation Operational Landsat Imager (OLI)
payload. Scheduled to launch in 2013, OLI provides imagery consistent with the historical Landsat spectral, spatial,
radiometric, and geometric data record and completes the generational technology upgrade from the Enhanced Thematic
Mapper (ETM+) whiskbroom technology to modern pushbroom technology afforded by advanced focal planes.
We explain how Ball’s capabilities allowed producing the innovative next-generational OLI pushbroom filter radiometer
that meets challenging radiometric accuracy or calibration requirements. OLI will improve the multi-decadal land
surface observation dataset dating back to the 1972 launch of ERTS-1 or Landsat 1.
KEYWORDS: Modulation transfer functions, Signal to noise ratio, Sensors, Radiometry, Systems modeling, Imaging systems, Digital filtering, Scanning probe microscopy, Point spread functions, Data modeling
Traditionally, optical remote sensing payload design satisfies highly defined specifications arrived at by consensus of the
scientific constituency. Designs are constrained by required performance such as resolution, Modulation Transfer
Function (MTF), and Signal-to-Noise-Ratio (SNR). Payload designers satisfy the specification by performing hardware
and cost trades. This process may lack continuous feedback between the performance of the scientific algorithms and the
payload design, potentially missing optimal design points.
The traditional method has produced separate and specific designs for imagery (over-sampling ratio Q > 0.8) vs.
radiometry (Q < 0.8). Radiometers are scientifically precise, with highly accurate scene collection over a tightly defined
pixel size exclusive of other scene points, often across several spectral channels. Imagers reveal sharper features, but
have considerable "bleeding" of scene radiance into adjacent pixels, causing errors in application of multispectral
Recently, we created end-to-end models that optimize end scientific data products by considering the payload design and
data processing algorithms together, rather than simply satisfying a payload specification. In this process, we uncovered
optimal payload design points and insights.
We explore end-to-end modeling results that show an optimal single converged payload design, and data processing
algorithms that produce simultaneous radiometer and imager products. We show how payload design choices for
Instantaneous Field of View (IFOV) and Ground Sampling Distance (GSD) maximize SNR for multiple data products,
resulting in an optimized design that increases flexibility of space assets. This approach is beneficial as we move towards
distributed and fused image systems.
Imaging instruments with state-of-the-art HgCdTe MWIR and LWIR detectors often have limited cooling resources. Therefore, they may need to deal with large detector dark currents and/or optics thermal emission currents. The sum of dark and thermal emission currents form an undesirable "offset" to the desired signal current, which can be orders of magnitude greater than the signal. With modest instrument thermal stability, the offset current change is small over instrument line imaging times on the order of 10 seconds. This allows cancellation or subtraction of the offset by injecting an equal and opposite current into the integration node. The exact value of this cancellation current can be simultaneously measured and stored for every pixel in a self calibrating deep space (negligible signal) scan cycle, leaving only the desired signal current when the aperture is subsequently scanned across the scene. Offset subtraction dramatically reduces the dynamic range requirements of the Readout Integrated Circuit (ROIC) signal chain at the cost of additional ROIC shot noise. However, this shot noise is rarely dominant in MWIR and LWIR applications so overall NEDT performance does not suffer. By subtracting the offset and dramatically reducing ROIC dynamic range requirements, the integration capacitor and overall ROIC size are greatly reduced, power dissipation is decreased, and linearity is greatly improved. The end result is similar NEDT performance at higher detector and instrument temperatures. An ROIC with automatic, low-noise, in unit cell offset subtraction has been developed and demonstrated with LWIR (15 micron cutoff) HgCdTe detectors operating at 67K. The offset, which is 20X the desired signal, is subtracted in less than 10 ms with better than 99% accuracy. The subtraction current drift is less than 0.0015%/s.