scholarly journals Detection Performance Analysis of the Standard FDA and FDA-MIMO Radar in the Gaussian Background

2021 ◽  
Vol 2021 ◽  
pp. 1-11
Author(s):  
Yongze Liu ◽  
Yuehong Ma ◽  
Haiming Jing
Keyword(s):  
Array Signal Processing ◽  
Signal To Noise Ratio ◽  
Mimo Radar ◽  
Detection Performance ◽  
Ratio Test ◽  
Test Statistics ◽  
Test Statistic ◽  
Processing Scheme ◽  
Radar Systems ◽  
Frequency Diverse Array

This paper studies the optimal detection performance of the standard frequency diverse array (FDA) radar and FDA multi-input multioutput (FDA-MIMO) radar in Gaussian clutter and noise. Array signal processing scheme at the receiver is firstly designed to obtain the array steering vector containing range, azimuth, and frequency increment. For the two array configurations, namely, collocated transmit-receive and collocated transmit distributed receive, the likelihood ratio test statistics and the test statistic distributions are derived in the Neyman–Pearson sense. It is then investigated how the number of array elements influences the detection performance of various radar systems at low signal-to-noise ratio (SNR). Several numerical simulations are carried out to demonstrate that the performance improvement is hard for MIMO and FDA-MIMO by only increasing the number of transmit elements, while it is achievable for the FDA. The paper finally makes a comparative analysis for detection performances of five radar configurations under different SNRs.

scholarly journals Compressive Detection Using Sub-Nyquist Radars for Sparse Signals

2016 ◽  
Vol 2016 ◽  
pp. 1-7
Author(s):  
Ying Sun ◽  
Jianjun Huang ◽  
Jingxiong Huang ◽  
Li Kang ◽  
Li Lei ◽  
...  
Keyword(s):  
Signal To Noise Ratio ◽  
Computation Time ◽  
Detection Performance ◽  
High Signal ◽  
Sparse Signals ◽  
Ratio Test ◽  
Digital Conversion ◽  
Real Time Processing ◽  
Analog To Digital ◽  
Analog To Digital Conversion

This paper investigates the compression detection problem using sub-Nyquist radars, which is well suited to the scenario of high bandwidths in real-time processing because it would significantly reduce the computational burden and save power consumption and computation time. A compressive generalized likelihood ratio test (GLRT) detector for sparse signals is proposed for sub-Nyquist radars without ever reconstructing the signal involved. The performance of the compressive GLRT detector is analyzed and the theoretical bounds are presented. The compressive GLRT detection performance of sub-Nyquist radars is also compared to the traditional GLRT detection performance of conventional radars, which employ traditional analog-to-digital conversion (ADC) at Nyquist sampling rates. Simulation results demonstrate that the former can perform almost as well as the latter with a very small fraction of the number of measurements required by traditional detection in relatively high signal-to-noise ratio (SNR) cases.

Multiway Contingency Tables: Monte Carlo Resampling Probability Values for the Chi-Squared and Likelihood-Ratio Tests

2010 ◽  
Vol 107 (2) ◽  
pp. 501-510 ◽  
Author(s):  
Michael A. Long ◽  
Kenneth J. Berry ◽  
Paul W. Mielke
Keyword(s):  
Monte Carlo ◽  
Likelihood Ratio ◽  
Contingency Table ◽  
Contingency Tables ◽  
Likelihood Ratio Tests ◽  
Ratio Test ◽  
Test Statistics ◽  
Test Statistic ◽  
Resampling Methods ◽  
Chi Squared

Monte Carlo resampling methods to obtain probability values for chi-squared and likelihood-ratio test statistics for multiway contingency tables are presented. A resampling algorithm provides random arrangements of cell frequencies in a multiway contingency table, given fixed marginal frequency totals. Probability values are obtained from the proportion of resampled test statistic values equal to or greater than the observed test statistic value.

scholarly journals Statistical Angular Resolution Limit for Ultrawideband MIMO Noise Radar

2015 ◽  
Vol 2015 ◽  
pp. 1-12
Author(s):  
Xiaoli Zhou ◽  
Hongqiang Wang ◽  
Yongqiang Cheng ◽  
Yuliang Qin ◽  
Haowen Chen
Keyword(s):  
Angular Resolution ◽  
Signal To Noise Ratio ◽  
Mimo Radar ◽  
Optimization Criterion ◽  
Ratio Test ◽  
Theoretic Approach ◽  
Resolution Limit ◽  
Factors Affecting ◽  
Noise Radar ◽  
The Relationship

The two-dimensional angular resolution limit (ARL) of elevation and azimuth for MIMO radar with ultrawideband (UWB) noise waveforms is investigated using statistical resolution theory. First, the signal model of monostatic UWB MIMO noise radar is established in a 3D reference frame. Then, the statistical angular resolution limits (SARLs) of two closely spaced targets are derived using the detection-theoretic and estimation-theoretic approaches, respectively. The detection-theoretic approach is based on the generalized likelihood ratio test (GLRT) with given probabilities of false alarm and detection, while the estimation-theoretic approach is based on Smith’s criterion which involves the Cramér-Rao lower bound (CRLB). Furthermore, the relationship between the two approaches is presented, and the factors affecting the SARL, that is, detection parameters, transmit waveforms, array geometry, signal-to-noise ratio (SNR), and parameters of target (i.e., radar cross section (RCS) and direction), are analyzed. Compared with the conventional radar resolution theory defined by the ambiguity function, the SARL reflects the practical resolution ability of radar and can provide an optimization criterion for radar system design.

scholarly journals Parameter Estimation and Target Detection of Phased-MIMO Radar Using Capon Estimator

2020 ◽  
Vol 20 (2) ◽  
pp. 60
Author(s):  
Syahfrizal Tahcfulloh ◽  
Muttaqin Hardiwansyah
Keyword(s):  
Parameter Estimation ◽  
False Alarm ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Mimo Radar ◽  
Detection Performance ◽  
Probability Of Detection ◽  
Detection Accuracy ◽  
Adaptive Estimator ◽  
Probability Of False Alarm

Phased-Multiple Input Multiple Output (PMIMO) radar is multi-antenna radar that combines the main advantages of the phased array (PA) and the MIMO radars. The advantage of the PA radar is that it has a high directional coherent gain making it suitable for detecting distant and small radar cross-section (RCS) targets. Meanwhile, the main advantage of the MIMO radar is its high waveform diversity gain which makes it suitable for detecting multiple targets. The combination of these advantages is manifested by the use of overlapping subarrays in the transmit (Tx) array to improve the performance of parameters such as angle resolution and detection accuracy at amplitude and phase proportional to the maximum number of detectable targets. This paper derives a parameter estimation formula with Capon's adaptive estimator and evaluates it for the performance of these parameters. Likewise, derivation for expressions of detection performance such as the probability of false alarm and the probability of detection is also given. The effectiveness and validation of its performance are compared to conventional estimator for other types of radars in terms of the effect of the number of target angles, the RCS of targets, and variations in the number of subarrays at Tx of this radar. Meanwhile, the detection performance is evaluated based on the effect of Signal to Noise Ratio (SNR) and the number of subarrays at Tx. The evaluation results of the estimator show that it is superior to the conventional estimator for estimating the parameters of this radar as well as the detection performance. Having no sidelobe makes this estimator strong against the influence of interference and jamming so that it is suitable and attractive for the design of radar systems. Root mean square error (RMSE) on magnitude detection from LS and Capon estimators were 0.033 and 0.062, respectively. Meanwhile, the detection performance for this radar has the probability of false alarm above 10-4 and the probability of detection of more than 99%.

scholarly journals Robust STAP for MIMO Radar Based on Direct Data Domain Approach

2017 ◽  
Vol 2017 ◽  
pp. 1-9
Author(s):  
Cheng Chen ◽  
Junjie He ◽  
Zeshi Yuan ◽  
Xiaohua Zhu ◽  
Hongtao Li
Keyword(s):  
Performance Optimization ◽  
Signal To Noise Ratio ◽  
Multiple Input Multiple Output ◽  
Admissible Solution ◽  
Mimo Radar ◽  
Detection Performance ◽  
Worst Case ◽  
Input Multiple Output ◽  
Direct Data ◽  
Direct Data Domain

The detection performance of direct data domain (D3) space-time adaptive processing (STAP) will be extremely degraded when there are mismatches between the actual and the presumed signal steering vectors. In this paper, a robust D3 STAP method for multiple-input multiple-output (MIMO) radar is developed. The proposed method utilizes the worst-case performance optimization (WCPO) to prevent the target self-nulling effect. An upper bound for the norm of the signal steering vector error is given to ensure that the WCPO problem has an admissible solution. Meanwhile, to obtain better detection performance in the low signal-to-noise ratio (SNR) environment, the proposed method gives a modified objective function to minimize the array noise while mitigating the interferences. Simulation results demonstrate the validity of our proposed method.

scholarly journals Garch Model Test Using High-Frequency Data

Mathematics ◽  
2020 ◽  
Vol 8 (11) ◽  
pp. 1922
Author(s):  
Chunliang Deng ◽  
Xingfa Zhang ◽  
Yuan Li ◽  
Qiang Xiong
Keyword(s):  
High Frequency ◽  
Garch Model ◽  
Wald Test ◽  
Asymptotic Distributions ◽  
High Frequency Data ◽  
Ratio Test ◽  
Test Statistics ◽  
Frequency Data ◽  
Test Statistic ◽  
Potential Applications

This work is devoted to the study of the parameter test for the Generalized Autoregressive Conditional Heteroskedasticity (GARCH) model. Based on the daily GARCH model, using the parameter estimator obtained by intraday high-frequency data, the adjusted Likelihood Ratio test statistic and Wald test statistic are provided. Asymptotic distributions of the two adjusted test statistics are deducted and a way to select the optimal sampling frequency is also discussed. Simulation studies show that the proposed test statistics have better size and power than traditional ones (without using intraday high-frequency data). An empirical study is given to illustrate the potential applications of the proposed tests. The results show the idea of this article is of certain superiority and it can be extended to other GARCH type models.

scholarly journals Low-Grazing Angle Detection in Compound-Gaussian Clutter with Hybrid MIMO Radar

2013 ◽  
Vol 2013 ◽  
pp. 1-8 ◽  
Author(s):  
Jincan Ding ◽  
Haowen Chen ◽  
Hongqiang Wang ◽  
Xiang Li ◽  
Zhaowen Zhuang
Keyword(s):  
Multiple Input Multiple Output ◽  
Grazing Angle ◽  
Mimo Radar ◽  
Ratio Test ◽  
Linear Quadratic ◽  
Signal Model ◽  
Radar Systems ◽  
Multiple Input ◽  
Multipath Effects ◽  
Input Multiple Output

This paper focuses on the target detection in low-grazing angle using a hybrid multiple-input multiple-output (MIMO) radar systems in compound-Gaussian clutter, where the multipath effects are very abundant. The performance of detection can be improved via utilizing the multipath echoes. First, the reflection coefficient considering the curved earth effect is derived. Then, the general signal model for MIMO radar is introduced in low-grazing angle; also, the generalized likelihood test (GLRT) and generalized likelihood ratio test-linear quadratic (GLRT-LQ) are derived with known covariance matrix. Via the numerical examples, it is shown that the derived GLRT-LQ detector outperforms the GLRT detector in low-grazing angle, and both performances can be enhanced markedly when the multipath effects are considered.

A Study of Clustering for the Enhancement of Image Resolution in Dynamic Photon Emission

2019 ◽  
Author(s):  
S. Chef ◽  
C. T. Chua ◽  
C. L. Gan
Keyword(s):  
Signal To Noise Ratio ◽  
Photon Emission ◽  
Optical Signal ◽  
Image Resolution ◽  
Time Dimension ◽  
Processing Scheme ◽  
3D Space ◽  
Initial Acquisition ◽  
Resolution Limits ◽  
Emission Microscopy

Abstract Limited spatial resolution and low signal to noise ratio are some of the main challenges in optical signal observation, especially for photon emission microscopy. As dynamic emission signals are generated in a 3D space, the use of the time dimension in addition to space enables a better localization of switching events. It can actually be used to infer information with a precision above the resolution limits of the acquired signals. Taking advantage of this property, we report on a post-acquisition processing scheme to generate emission images with a better image resolution than the initial acquisition.

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