Ambiguity Surface Statistics and Overcontainment.
Abstract
Cross-correlation algorithms can be used to detect a signal that is common to both channels. The current understanding of the performance of cross-correlation algorithms is based on the assumption that the processing and signal bandwidths are equal. Under these conditions, it is well known that the signal-to-noise power ratio (SNR) required to achieve a desired performance decreases as the integration time increases. However, in practice, it is usually necessary to use a processing bandwidth that is larger than the signal bandwidth (called signal overcontainment) because the signal bandwidth or the signal center frequency are only known approximately. The detection performance of cross-correlation algorithms is derived for the signal over-containment case. It is shown that the SNR can be decreased by increasing the signal overcontainment for small signal 'time-bandwidth' products. It is also shown that for moderate to large signal 'time-bandwidth' products, the SNR increases with increasing signal overcontainment, but that the SNR increases very slowly with increasing signal overcontainment. Image filtering algorithms can be used to enhance the features of an ambiguity surface and thereby improve the detection performance. The PFA at the output of these filters is easily related to the single cell threshold when the noise cells are independent.
Document Details
- Document Type
- Technical Report
- Publication Date
- Sep 30, 1981
- Accession Number
- ADA108762
Entities
People
- Joseph Lapointe Jr