This article has been accepted for inclusion in a future issue of this journal. Content is final as presented, with the exception of pagination. IEEE GEOSCIENCE AND REMOTE SENSING LETTERS 1 Maximum–Minimum Eigen Detector for Ionospheric Irregularities Over Low-Latitude Region Swapna Raghunath, Member, IEEE, and D. Venkata Ratnam, Senior Member, IEEE Abstract— Plasma irregularities are a predominant feature over the low-latitude ionosphere within 20° north and south of the geomagnetic equator. The range delay errors introduced in the global navigation satellite system (GNSS) and in the space-based augmentation system by the plasma irregularities are difficult to measure due to the unpredictable nature of ionosphere. This letter presents a maximum–minimum eigen algorithm that has been developed for the efficient detection of ionospheric irregu- larities in the low latitudes. GNSS data were collected from five stations spread over the Indian terrain for the solar maximum year of 2013 and real-time detection of plasma irregularities was performed. The five GNSS stations, namely, Pbr2, Iisc, Guntur, Hyde, and Lck2 span over the geomagnetic latitudes ranging from 2.07° N to 17.92° N. The results show a very good correlation with the equatorial ionospheric disturbances. The occurrence of plasma irregularities was found to be a maximum at the ionospheric anomaly crest. Index Terms— Eigenvalues, equinox, ionospheric irregularities, plasma bubbles, solar maximum and solstice. I. I NTRODUCTION S TANDALONE global navigation satellite system (GNSS) is vulnerable to interference and does not fully satisfy the requirements of precise-positioning services like aircraft navi- gation, missile guidance, and so on [1]. Space-based augmen- tation system (SBAS) compensates for the drawbacks of GNSS by providing ionospheric range delay corrections and integrity bounds, thus enhancing its availability, accuracy, continuity, and integrity in civil aviation. The occurrence of equatorial plasma bubbles and the consequent scintillations even during geomagnetically quiet periods, cause large amplitude fades resulting in temporary loss of GNSS and SBAS signal avail- ability [2]. Paznukhov et al. [3] gave a detailed account of the dependence of plasma bubble occurrence on local time, season and longitude over equatorial Africa. Paznukhov et al. [3] Manuscript received March 23, 2016; revised August 13, 2016, January 11, 2017, and March 7, 2017; accepted March 15, 2017. This work was supported in part by the NavIC–GAGAN Utilization Programme at the Space Applica- tions Centre, Ahmedabad, ISRO India, through the project titled Development of Single Frequency Ionospheric correction and plasma bubble detection algorithms using GAGAN & NavIC TEC observations under Project NGP-10 and in part by the Department of Science and Technology, New Delhi, India, through the SR/FST/ESI-130/2013(C) FIST program. S. Raghunath is with the Department of Electronics and Communica- tions Engineering, G. Narayanamma Institute of Technology and Science, Hyderabad 500104, India, and also with Jawaharlal Nehru Technological University, Hyderabad 500085, India (e-mail: swapna.karnam1@gmail.com). D. V. Ratnam is with the Department of Electronics and Communications Engineering, Koneru Lakshmaiah University, Guntur 522502, India (e-mail: dvratnam@kluniversity.in). Color versions of one or more of the figures in this letter are available online at http://ieeexplore.ieee.org. Digital Object Identifier 10.1109/LGRS.2017.2687079 reported that the plasma instabilities showed a pronounced increase after sunset and that the scintillations were stronger during equinoctial months. Similar reports were published for Brazil and India, where the plasma bubble generation and evolution presented a strong dependence on the solar flux and usually occurred within the window of 18–24 h local time [4]–[6]. Huang et al. [7] and Chu et al. [8] have demonstrated a significant increase in the probability of occurrence of equatorial plasma bubbles during peak activity periods of the 22nd and 23rd solar cycles, respectively. El-Arini and Lejeune [9] applied a likelihood ratio test for the detection of ionospheric plasma irregularities that yielded the maximum probability of detection for a given probability of false alarm ( P fa ). Likelihood ratio test requires a complete knowledge of the probability distribution of the observed para- meter. In ionospheric irregularity detection, the observation parameter to be considered is the total electron content (TEC), which varies randomly during disturbances, without conform- ing to a particular probability distribution function, causing the implementation of logarithm of likelihood ratio test to be extremely tiresome. Raghunath and Ratnam [6] devised a fast Fourier transform averaging ratio (FAR) algorithm for the detection of the GNSS satellites that were affected by the ionospheric plasma density irregularities over the low latitude region of south India during the 2013 solar maximum. FAR algorithm suffers from the drawback that it may not be able to detect the affected satellites when the signals from most of them are corrupted by the irregularities in the ionosphere [6]. There is a need for a more effective plasma inhomogeneity detection algorithm over the low latitude ionosphere. Zeng and Liang [10] developed a maximum–minimum eigenvalue (MME) detection algorithm for spectrum sensing in cognitive radio. Later, Liu et al. [11] and Abed and Shahzadi [12] proposed variations to the MME algorithm for the detection of available channels in cognitive radio problems. The presence of energy or signal in a channel is found by computing the ratio of the maximum to the minimum eigenvalue of the received signal covariance matrix and comparing it with a threshold. The presence of a stronger signal in the channel has higher probability of exceeding the threshold as opposed to a weak signal or no signal. In signal processing problems eigen decompositions are usually applied to covariance matrices wherein the eigenvalues are a measure of the magnitude of variance in the data. In this letter, the MME algorithm has been adapted for the detection of the irregularities in the ionospheric plasma. An ionospheric plasma irregularity is detected by considering the decision criterion as the ratio of the maximum eigenvalue to the 1545-598X © 2017 IEEE. Personal use is permitted, but republication/redistribution requires IEEE permission. See http://www.ieee.org/publications_standards/publications/rights/index.html for more information.