Nonstationary signal design for coexisting radar and communications systems

Kota, John; Jacyna, Garry M.; Papandreou-Suppappola, Antonia

doi:10.1109/acssc.2016.7869101

Cited by 6 publications

(8 citation statements)

References 17 publications

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“…It may be possible to improve the aforementioned performance tradeoff when the time-varying phase function is also used in the design, especially at varying output SNR values. As we demonstrated in References [17,21] using a deviation measure of the Barankin bound from the Cramér–Rao lower bound on the estimated target state covariance, waveforms with a logarithmic phase function result in lower MSE than waveforms with a quadratic phase function.…”

Section: Discussionmentioning

confidence: 93%

“…In particular, it has been well-established that radar transmit waveforms with quadratic time-varying phase function improve range resolution in radars [39]. We have also recently demonstrated that these waveforms improve radar MSE performance under low signal-to-interference-plus-noise ratio (SINR), and in particular, in the presence of high communications interference [17,21]. As a result, we first concentrated on a performance metric that is specific only to MU communications systems: We applied waveforms with quadratic time-varying phase function to reduce MAI.…”

Section: Waveform-dependent Performance Optimization Methodsmentioning

confidence: 99%

“…Following the proposed CoWS design, the m th commications user is assigned the OLFM waveform sm(t) = snormalc,m(t) in Equation (4) with duration T = Tnormalc and a unique FM rate bm that must satisfy:bm=B2Tc−()M−mTc20.166667em,1.emm=1,…,M0.166667em,for minimum MAI, following Equation (6) [21,40], for a given bandwidth B . The maximum number of users transmitting at the same time with an assigned unique FM rate is M = ⌊TcB/2⌋ (see Section 2).…”

Section: Waveform-dependent Performance Optimization Methodsmentioning

confidence: 99%

“…Various methods have been considered in designing the transmit waveforms of different systems that share spectra. Codesign methods construct the transmit waveform of one system to minimize strong interference caused by other systems [17,18,19,20,21]. Coexistence methods, on the other hand, design a joint transmit waveform for multiple spectrum sharing systems.…”

Section: Introductionmentioning

confidence: 99%

“…Various such approaches were developed for coexisting radar and communications systems [18,22,23,24,25,26,27,28,29]. For example, both systems shared orthogonal frequency division multiplexing signaling in References [22,23] and linear frequency-modulated chirp signaling in References [24,25,26]. In Reference [27], radar and communications coexistence was achieved using joint channel estimation and adaptive parameter optimization, whereas maximization of the combined mutual information was used in Reference [28].…”

Section: Introductionmentioning

confidence: 99%

See 4 more Smart Citations

Joint Design of Transmit Waveforms for Object Tracking in Coexisting Multimodal Sensing Systems

Kota

Papandreou-Suppappola

2019

Sensors

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We examine a multiple object tracking problem by jointly optimizing the transmit waveforms used in a multimodal system. Coexisting sensors in this system were assumed to share the same spectrum. Depending on the application, a system can include radars tracking multiple targets or multiuser wireless communications and a radar tracking both multiple messages and a target. The proposed spectral coexistence approach was based on designing all transmit waveforms to have the same time-varying phase function while optimizing desirable performance metrics. Considering the scenario of tracking a target with a pulse–Doppler radar and multiple user messages, two signaling schemes were proposed after selecting the waveform parameters to first minimize multiple access interference. The first scheme is based on system interference minimization, whereas the second scheme explores the multiobjective optimization tradeoff between system interference and object parameter estimation error. Simulations are provided to demonstrate the performance tradeoffs due to different system requirements.

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Section: Discussionmentioning

confidence: 93%

Section: Waveform-dependent Performance Optimization Methodsmentioning

confidence: 99%

Section: Waveform-dependent Performance Optimization Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Joint Design of Transmit Waveforms for Object Tracking in Coexisting Multimodal Sensing Systems

Kota

Papandreou-Suppappola

2019

Sensors

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Multibeam radar based on linear frequency modulated waveform diversity

Kocjancic

Balleri

Merlet

2018

IET Radar, Sonar & Navigation

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Multibeam radar (MBR) systems based on waveform diversity require a set of orthogonal waveforms in order to generate multiple channels in transmission and extract them efficiently at the receiver with digital signal processing. Linear frequency modulated (LFM) signals are extensively used in radar systems due to their pulse compression properties, Doppler tolerance and ease of generation. In this paper, we investigate the level of isolation between MBR channels based on LFM chirps with rectangular and Gaussian amplitude envelopes. The orthogonal properties and the mathematical expressions of the isolation are derived as a function of the chirp design diversity, and specifically for diverse frequency slopes and frequency offsets. The analytical expressions are validated with a set of simulations as well as with experiments at C-band using a rotating target.

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