Digital antenna array

The development and practical realization of digital antenna arrays theory started in 1962 under the guidance of Vladimir Varyukhin (USSR).

[1] The implementation of effective signal processing in radars by the end of the 1950s predetermined the use of electronic computers in this field.

In 1957, Ben S. Meltont and Leslie F. Bailey published article[2] regarding using algebraic operations for signal processing with the help of electronic circuits or analog computer.

[1] Three years after in 1960 the idea of using high-speed computers to solve directional finding problems was embodied, initially to locate earthquake epicenter.

Then, it was needed only to solve the problem of direct digital data input into the computer from sensors, excluding the step of preparation of punch card and operator assistance as a surplus element.

[1] This step for radars theory was made after 1962 in the former USSR conducted with a solution to the problem of superRayleigh resolution of the emission sources.

The signals from every direction can be estimated simultaneously and integrated for a longer time to increasing of signals energy when detecting far-off objects and simultaneously integrated for a shorter time to detecting fast-moving close objects.

[6] Before digital beamforming operation should be used a correction of channels characteristics by a special test source or using the heterodyne signal.

[10] Limitations on the accuracy of estimation of direction of arrival signals and depth of suppression of interferences in digital antenna arrays are associated with jitter in ADCs and DACs.

[11][12] In maximum likelihood beamformer (DML), the noise is modeled as a stationary Gaussian white random processes while the signal waveform as deterministic (but arbitrary) and unknown.

The Bartlett beamformer is a natural extension of conventional spectral analysis (spectrogram) to the DAA.

The MVDR/Capon beamformer can achieve better resolution than the conventional (Bartlett) approach, but this algorithm has higher complexity due to the full-rank matrix inversion.

Technical advances in GPU computing have begun to narrow this gap and make real-time Capon beamforming possible.

The important trend in evolving digital signal processing for DAA is the use of Artificial Intelligence technologies.

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