Military researchers ask industry to develop digital signal processing for advanced radar phased arrays

Jan. 9, 2024
Digital architectures can support simultaneous beams, yet have evolved using algorithms for signal processing that typically are for analog arrays.

ARLINGTON, Va. – U.S. military researchers are asking industry to develop advanced sensor processing for radar digital phased arrays of different sizes and bandwidths.

Officials of the U.S. Defense Advanced Research Projects Agency (DARPA) in Arlington, Va., have issued a solicitation (DARPA-PS-24-05) for the Scalable On Array Processing (SOAP) project.

SOAP seeks to develop scalable software algorithms that replace large matrix operations in digital signal processing with the codesign of distributed processing hardware to support the rapid and efficient execution of the algorithms.

The target application of the effort will be elemental digital phased arrays scaled to arbitrary sizes and bandwidths. Novel processing approaches adapted from disciplines outside of radar and phased arrays are of particular interest.

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Digital array architectures have advantages over analog arrays, notably the ability to support several simultaneous beams and functions. Yet digital arrays have evolved using algorithms for signal processing and tracking that typically are for analog arrays.

Digital bottlenecks from traditional array computations have limited development of digital arrays. Phased arrays larger than 1000 elements and instantaneous bandwidths of 1 GHz can require the real time numerical inversion of 1000 x 1000 matrices, with greater than 1 terabit per second of data between the array front end and intermediate processor stages.

This has resulted in digital bottlenecks, which limit the number of independent elements and instantaneous bandwidths achievable in today’s digital array architectures.

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Current digital arrays do most of their processing on a centralized back-end processor, which often requires many racks of equipment and consumes thousands of Watts of power. At the same time, this centralized approach requires all of the array data to be moved off the array, creating data movement bottlenecks.

Instead, SOAP seeks to do scalable algorithms and processing to overcome digital bottlenecks, and develop new approaches to array operations for large amounts of data in applications like machine vision, and large language model training.

SOAP aims to reduce computational complexity, and move the processing from physically separated back-end processors to processors integrated into the array by designing processors that can be distributed within the array, as close to the elements as possible. These processors should be networked such that the data from any element can be processed by any processor.

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SOAP has two technical challenges: Realizing scalable algorithms for digital array computations; and realizing processing architectures that can scale to extremely large aggregate data rates.

The SOAP project should start around next September, and several contract awards are expected. Companies interested should submit abstracts no later than 17 Jan. 2023 to the DARPA BAA website at Submit full proposals to the DARPA BAA website no later than 4 March 2024.

More information is online at

About the Author

John Keller | Editor

John Keller is editor-in-chief of Military & Aerospace Electronics magazine, which provides extensive coverage and analysis of enabling electronic and optoelectronic technologies in military, space, and commercial aviation applications. A member of the Military & Aerospace Electronics staff since the magazine's founding in 1989, Mr. Keller took over as chief editor in 1995.

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