Performance Prediction for Coherent Noise Radars Using the Correlation Coefficient

Luong, David; Balaji, Bhashyam; Rajan, Sreeraman

doi:10.1109/access.2021.3135292

Cited by 18 publications

(30 citation statements)

References 16 publications

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“…Fig. 10 shows ROC curve plots for the 𝐷 DN detector, together with approximations obtained from (41). We see that the approximation is good for small values of 𝜌, but (41) overestimates the performance of the detector when 𝜌 is large.…”

Section: Remarkmentioning

confidence: 95%

“…To see this, consider the ROC curve for ρ in the form (32); this is a good approximation to (25) when 𝑁 is large. When 𝜌 1, the 𝜌 2 terms in (32) may be ignored; the result is exactly (41). Hence, under the stated conditions, the two detectors are essentially equivalent.…”

Section: Comparison Of Roc Curves For ρ and 𝐷 Dnmentioning

confidence: 99%

“…We should note that the conditions 𝑁 → ∞ and 𝜌 1 have more than a purely mathematical significance. In fact, the correlation coefficient 𝜌 is a decreasing function of range [41]; it also depends on factors such as the radar cross section of the target. Thus, the small-𝜌 limit corresponds to the case where the target of the radar is small or far away.…”

Section: Comparison Of Roc Curves For ρ and 𝐷 Dnmentioning

confidence: 99%

“…Fig.10. ROC curves for 𝐷 DN , together with approximations calculated using(41). In (a), 𝑁 = 10 and 𝜌 ∈ {0.2, 0.4, 0.6, 0.8}; in (b), 𝜌 = 0.2 and 𝑁 ∈ {10, 50, 100, 200}.…”

mentioning

confidence: 99%

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Structured Covariance Matrix Estimation for Noise-Type Radars

Luong,

Balaji,

Rajan

2022

Preprint

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Standard noise radars, as well as noise-type radars such as quantum two-mode squeezing radar, are characterized by a covariance matrix with a very specific structure. This matrix has four independent parameters: the amplitude of the received signal, the amplitude of the internal signal used for matched filtering, the correlation between the two signals, and the relative phase between them. In this paper, we derive estimators for these four parameters using two techniques. The first is based on minimizing the Frobenius norm between the structured covariance matrix and the sample covariance matrix; the second is maximum likelihood parameter estimation. The two techniques yield the same estimators. We then give probability density functions (PDFs) for all four estimators. Because some of these PDFs are quite complicated, we also provide approximate PDFs. Finally, we apply our results to the problem of target detection and derive expressions for the receiver operating characteristic curves of two different noise radar detectors.

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Section: Remarkmentioning

confidence: 95%

Section: Comparison Of Roc Curves For ρ and 𝐷 Dnmentioning

confidence: 99%

Section: Comparison Of Roc Curves For ρ and 𝐷 Dnmentioning

confidence: 99%

mentioning

confidence: 99%

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Structured Covariance Matrix Estimation for Noise-Type Radars

Luong,

Balaji,

Rajan

2022

Preprint

Self Cite

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“…The error probability is obtained in two parts corresponding to the absence or presence of the target (the false-alarm probability f P and the miss probability r P ). The error probability in quantum receivers is [15,[34][35][36][37][38][39][40][41][42][43][44][45]:…”

Section: Post-processingmentioning

confidence: 99%

Design and simulation of engineered Josephson parametric amplifier in quantum two-mode squeezed radar

Norouzi

Hosseiny

Seyed-Yazdi

et al. 2022

Preprint

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Josephson parametric amplifier (JPA) engineering is a significant component in the quantum two-mode squeezed radar (QTMS), to enhance, for instance, radar performance and the detection range or bandwidth. In this study, we apply quantum theory to a research domain focusing on the simulation of QTMS radar. We simulate a proposal of using engineered JPA (EJPA) to enhance the performance of a QTMS radar. We define the signal-to-noise ratio (SNR) and detection range equations of the QTMS radar. The engineered JPA leads to a remarkable improvement of the quantum radar performance, i.e. a large enhancement in SNR of about 6 dB more than the conventional QTMS radar (with respect to the latest version of QTMS radar, and not to classical radar), a substantial improvement in the probability of detection through far fewer channels. Finally, we simulate signal transmission to target in QTMS radar and achieve a huge increase in QTMS radar range, from half a meter in the conventional JPA to 482 m in the current study.

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Purity in the QTMS radar

Hosseiny

Norouzi

Seyed-Yazdi³

et al. 2023

Phys. Scr.

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In this paper, we analyze the purity and decoherence effects in quantum two-mode squeezed (QTMS) radar as a function of the squeezing parameter and temperature, using quantum information processing tools. The squeezing parameter is an important key to improving the performance of the QTMS radar. We investigate the response to the squeezing parameter controlling to system state of the QTMS radar. In this work, we deal with the QTMS radar with two cases of the transmitted signal, the presence or the absence of the target. The squeezing parameter controls the power of the generated signal and idler, the correlation between signal and idler, as well as the coherence and state of the system. We show that the decoherence effects are low at low temperatures, low squeezing parameters, and low power. In addition, we demonstrate that the purity and, consequently, the coherence of the QTMS radar are better when the target is absent than when it is present. However, the coherence and purity are maintained at high temperatures in both cases. In addition, by calculating the entropy of formation as a tool to investigate the qualitative behavior of entanglement in QTMS radar, we show that the behaviors of purity and entropy are similar. Finally, we show that the proportion of received photons in the QTMS radar is an important factor in improving the radar performance.

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Performance Prediction for Coherent Noise Radars Using the Correlation Coefficient

Cited by 18 publications

References 16 publications

Structured Covariance Matrix Estimation for Noise-Type Radars

Structured Covariance Matrix Estimation for Noise-Type Radars

Design and simulation of engineered Josephson parametric amplifier in quantum two-mode squeezed radar

Purity in the QTMS radar

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