Generalized Ambiguity Function for MIMO Radar Systems

Ilioudis, Christos; Clemente, Carmine; Proudler, Ian K.; Soraghan, John J.

doi:10.1109/taes.2019.2907390

Cited by 12 publications

(2 citation statements)

References 28 publications

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“…In work [26] a generalized signal model is presented to accommodate both narrowband and wideband signals in a multi-input multi-output (MIMO) sensor system scenarios. the proposed formulation is parameterized using the signal and channel correlation matrices to account for different waveform and sensor placement designs, thereby allowing a flexible modelling approach.…”

Section: Literature Data Analysis and Problem Formulationmentioning

confidence: 99%

Method of assessment of frequency resolution for aircraft

Yevseiev

Herasymov

Kuznietsov

et al. 2023

EEJET

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The object of the study is to evaluate the quality of the frequency distribution of aircraft, which characterizes the effectiveness of radar surveillance of aircraft and determines the effectiveness of their control using radio signals. The frequency resolution of an aircraft is usually studied using the frequency ambiguity function for a coherent packet of radio pulses. However, there is a problem of estimating phase fluctuations, which is caused by the heterogeneity of the propagation of radio pulses, which affects the functioning of radar stations under different atmospheric conditions. A feature of the study is the development of theoretical provisions for the process of detection and radio control of single aircraft under the organized action of swarms. A normalized frequency ambiguity function is obtained, which takes into account the transformations caused by the radial motion of the aircraft. The calculations made it possible to estimate the range of changes in the frequency distribution under the condition of the additive effect of the internal noise of the radar receiver and the multiplicative effect of the cartelized phase fluctuations of the control radio signal. The statistical characteristics of phase fluctuations of radio pulses were obtained, under which their influence on the operation of radio technical control and radar systems is the most significant. Such statistical characteristics are important for the theory of radar location and of practical importance for the improvement of radio control of objects. Method is proposed for numerical evaluation of the influence of atmospheric disturbances on the frequency distribution function of aircraft during flight. This method is a convenient tool for analyzing the quality of the frequency distribution of a radar station in various conditions of radar surveillance of single aircraft in their organized swarm action.

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Section: Literature Data Analysis and Problem Formulationmentioning

confidence: 99%

Method of assessment of frequency resolution for aircraft

Yevseiev

Herasymov

Kuznietsov

et al. 2023

EEJET

View full text Add to dashboard Cite

show abstract

“…The AF is not uniquely defined [8,9], including in the works of Woodward [6]. Further, later works have generalized this definition to handle larger bandwidth signals [10,11], long duration signals [12], volumetric scatterers [13,14], targets with high velocity [15,16], and angular domain [17][18][19]. The AF is also used in other applications such as optics [20][21][22].…”

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confidence: 99%

Phase Retrieval for Radar Waveform Design

Pinilla¹,

Mishra²,

Sadler³

et al. 2022

Preprint

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The ability of a radar to discriminate in both range and Doppler velocity is completely characterized by the ambiguity function (AF) of its transmit waveform. Mathematically, it is obtained by correlating the waveform with its Doppler-shifted and delayed replicas. We consider the inverse problem of designing a radar transmit waveform that satisfies the specified AF magnitude. This process can be viewed as a signal reconstruction with some variation of phase retrieval methods. We provide a trust-region algorithm that minimizes a smoothed non-convex least-squares objective function to iteratively recover the underlying signal-of-interest for either time-or band-limited support. The method first approximates the signal using an iterative spectral algorithm and then refines the attained initialization based upon a sequence of gradient iterations. Our theoretical analysis shows that unique signal reconstruction is possible using signal samples no more than thrice the number of signal frequencies or time samples. Numerical experiments demonstrate that our method recovers both time-and band-limited signals from even sparsely and randomly sampled AFs with mean-square-error of 1×10 −6 and 9 × 10 −2 for the full noiseless samples and sparse noisy samples, respectively.

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