Generative Adversarial Network for Variable-Length Sensing Waveform Synthesis

Vesa Saarinen, Visa Koivunen

Research output: Chapter in Book/Report/Conference proceedingConference contributionScientificpeer-review


We propose a generative adversarial network (GAN) system for synthesizing multiple families of novel radar waveforms with desirable Ambiguity Function (AF) shapes as well as a constant modulus property. Additionally, we introduce a penalty term to promote a low cross-correlation among synthesized waveforms. Many commonly-used radar code families contain only a limited number of sequences of a certain length. In modern radar applications, such as multifunction, MIMO, and cognitive radars, this may reduce the achievable performance gains. These systems launch multiple waveforms simultaneously in order to deal with low observable targets or large numbers of small targets. Therefore, the synthesis of novel waveforms and waveform families is important. Generating new waveforms on demand is also beneficial in scenarios where an adversary attempts to detect or recognize launched waveforms. We develop a conditional Wasserstein GAN (WGAN) for multiple datasets of complex-valued input data with varying code lengths. For each dataset, the model aims to synthesize waveforms with the same length and AF shape as the waveforms in that dataset. The model is trained to synthesize two classes of waveforms with different lengths using Frank and Oppermann codes. The AF shapes of synthesized waveforms are nearly identical to those of the training data. Additionally, the proposed penalty term allows for a tradeoff between the AF fidelity of synthesized samples and the expected cross-correlation among synthesized waveforms.
Original languageEnglish
Title of host publication2021 IEEE 22nd International Workshop on Signal Processing Advances in Wireless Communications (SPAWC)
Number of pages5
ISBN (Electronic)978-1-665-42851-4
ISBN (Print)978-1-6654-2852-1
Publication statusPublished - 15 Nov 2021
MoE publication typeA4 Article in a conference publication
EventIEEE International Workshop on Signal Processing Advances in Wireless Communications - Lucca, Italy
Duration: 27 Sep 202130 Sep 2021
Conference number: 22

Publication series

ISSN (Electronic)1948-3252


WorkshopIEEE International Workshop on Signal Processing Advances in Wireless Communications
Abbreviated titleSPAWC


  • Training
  • Wireless communication
  • Codes
  • Shape
  • Training data
  • Signal processing
  • Generative adversarial networks


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