Principles and Applications of Random FM Radar Waveform Design

Blunt, Shannon D.; Jakabosky, John; Mohr, Charles A.; McCormick, Patrick M.; Owen, Jonathan W.; Ravenscroft, Brandon; Şahin, Cenk; Zook, Garrett; Jones, Christian C.; Metcalf, Justin G.; Higgins, Thomas

doi:10.1109/maes.2019.2953763

Cited by 36 publications

(7 citation statements)

References 27 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Minimisation of the complementary aggregated sidelobes in ( 16) is a non-convex problem and global optimality cannot be guaranteed. However, in keeping with the spirit of random FM waveforms [28], it is not the single best solution sought, but rather a diverse set of sufficiently good solutions that further benefit from incoherent sidelobe combining when slow-time (Doppler) processing is subsequently performed. Therefore, instead of an optimal, yet brittle, result that is sensitive to degradation when inevitable mismatch arises, a sub-optimal result is obtained that is more robust to these mismatch effects by virtue of simple coherent averaging.…”

Section: Complementary Fm Waveform Designmentioning

confidence: 99%

“…From a particular outlook, Comp‐FM waveforms may be viewed as a generalisation of complementary coding. Specifically, where the latter achieves sidelobe cancellation by exploiting the additional degrees of freedom provided by a pair of (or in general N ) different waveforms, Comp‐FM belongs to a growing family of “random FM” waveforms, whereby every pulse possesses a unique waveform that is not repeated (see [28] for an overview). The benefit of non‐repetition in this context is that, while unique subsets of waveforms can be designed for sidelobe cancellation via complementary combining, the overall coherent processing interval (CPI) is comprised of distinct subsets that provide even further sidelobe reduction by virtue of incoherent sidelobe averaging.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Complementary frequency modulated radar waveforms and optimised receive processing

Jones

Mohr

McCormick

et al. 2021

IET Radar Sonar & Navi

Self Cite

View full text Add to dashboard Cite

Design methodologies are developed for complementary frequency modulated (FM) waveforms and for optimised complementary mismatched filtering (MMF) of arbitrary non-repeating waveforms. The former is a sub-class of random FM waveforms denoted as complementary FM (Comp-FM) while the latter extends a practical instantiation of least-squares mismatched filtering yielding the mismatched complementary-on-receive filtering (MiCRFt) scheme. Both of these approaches have an emphasis on the nonideal physical effects of the radar transmitter and receiver, thereby permitting highfidelity simulation analysis and subsequent experimental demonstration of their efficacy using open-air measurements.This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.

show abstract

Section: Complementary Fm Waveform Designmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Complementary frequency modulated radar waveforms and optimised receive processing

Jones

Mohr

McCormick

et al. 2021

IET Radar Sonar & Navi

Self Cite

View full text Add to dashboard Cite

show abstract

“…Adaptive radar, or cognitive radar, has been applied to a diverse set of radar sensing problems. Adaptive methods have been shown effective at producing spectrally notched waveforms for spectrum sharing [15,16], incorporating a priori knowledge of the environment [17], adapting radar parameters in response to target statistics [18][19][20] and other applications [21,22]. Several recent advancements in the field of adaptive radar are detailed in Refs.…”

Section: Introductionmentioning

confidence: 99%

Information theoretic waveform design with applications to adaptive‐on‐transmit radar

Herr,

Raju,

Stiles

2023

IET Radar Sonar & Navi

View full text Add to dashboard Cite

The marginal Fisher information (MFI) metric is used to design waveforms for the sake of informationally optimal adaptive‐on‐transmit radar operation. A framework for MFI waveform design is developed and the Polyphase‐Coded FM (PCFM) waveform model is utilised to produce a constant‐modulus, spectrally contained signal amenable to transmission with high‐power amplifiers. The efficacy of the MFI waveform design and minimum mean square error (MMSE) estimation is experimentally demonstrated and extended into an adaptive and dynamic sensing paradigm. The radar transmit waveform is optimised to maximise the Fisher information with respect to the range profile. Upon observing new information from radar echoes, the iterative MMSE (iMMSE) estimator then minimises the estimation error variance according to prior observations. Sequential information maximisation (via waveform design) and error minimisation (via iMMSE) tends towards the Cramér–Rao lower bound (CRLB) with additional measurements improving radar resolution and accuracy. These concepts maximise the information extracted by a radar operating in a congested spectrum where the available bandwidth is limited.

show abstract

“…Previously, pulse diversity has received attention in SLL reduction for PM waveforms [14]. Additionally, diverse random FM [15] and LFM [16] waveforms have been proposed as well. These references describe various advantages of using diverse pulse trains, but do not deal with reducing the SLL in a systematic way.…”

Section: Introductionmentioning

confidence: 99%

Range Sidelobe Level Reduction With a Train of Diverse LFM Pulses

Neuberger

Vehmas²

2022

IEEE Trans. Aerosp. Electron. Syst.

View full text Add to dashboard Cite

Target masking is a pervasive problem in radar signal processing: the range sidelobes of the waveform's matched filter response may cause a strong target to prevent the detection of nearby weaker targets. Common solutions to sidelobe level reduction for frequency modulated waveforms result in an SNR loss. In this correspondence, we propose a novel method using pulse diversity to reduce the range sidelobes while avoiding SNR loss. The proposed approach is based on shaping the power spectrum of the summation of a train of constant-amplitude linearly frequency modulated pulses to resemble a Gaussian function. We present a numerical example demonstrating a drastic sidelobe level reduction. Importantly, our approach avoids any processing SNR loss.

show abstract

Principles and Applications of Random FM Radar Waveform Design

Cited by 36 publications

References 27 publications

Complementary frequency modulated radar waveforms and optimised receive processing

Complementary frequency modulated radar waveforms and optimised receive processing

Information theoretic waveform design with applications to adaptive‐on‐transmit radar

Range Sidelobe Level Reduction With a Train of Diverse LFM Pulses

Contact Info

Product

Resources

About