Image understanding of oblique ionograms: the autoscaling problem

Abstract

Salisbury, South Australia, 5 108 Nick-Redding @ ds to. defence. gov. au ph. +61 8 259 7058 fax 5200 ABSTRACT This paper presents an image understanding system for oblique ionograms, which are a two-dimensional measurement of the high-frequency properties of the ionosphere. The system for image understanding of oblique ionograms (called "autoscaling") presented here involves three stages. Firstly, the ionogram is filtered by estimating the noise in each pixel of the image by fitting orthogonal second-order multinomials to its 3 by 3 neighbourhood. Secondly, feature vectors for each trace of the filtered ionogram are extracted using a process of thinning, trimming, model fitting, and a final merging stage that accounts for broken traces. The model used for ionogram traces is an implicit quartic equation, and is fitted to the cleaned-up skeleton of the trace using orthogonal distance regression. A third stage of the overall system uses the feature vectors to identify the prominent modes and other important features of the ionogiams, and to track these modes and features as they evolve across sequences of ionograms. This work will automate the task of identifying and tracking ionospheric propagation modes in oblique ionograms. The resulting system will be used to process current data streams to extract large volumes of significant information: this will help the understanding of ionospheric processes and can be used as input to automatic frequency management systems for communications networks.

Real-time automatic scaling method of oblique ionogram parameters based on morphological operator and inversion technique

“…The method in Ref. [9] is only suitable for the ionogram with one high angle wave. Fan et al [10] used morphological operators in digital image processing to identify E layer trace, O-mode trace and X-mode trace from F 2 layer.…”

“…Up to date, the public references about oblique ionogram automatic scaling are few. Redding (1996) [9] used several steps to complete the oblique ionogram automatic scaling. These steps include filtering noise, refining traces, model fitting and merging traces.…”

An automatic scaling method for obtaining the trace and parameters from oblique ionogram based on hybrid genetic algorithm

“…Up to now, the published papers related to scaling oblique ionogram are few [ Redding , ; Fan et al ., ; Settimi et al ., ; Ippolito et al ., ]. Redding [] extracted the traces of oblique ionograms by adopting digital image processing method which includes series of steps: filter noise, refine trace, amend trace, and merge trace. Fan et al .…”

Automatic Recognition Method of Layer Paths in the Ionogram Based on Mathematical Morphology Method and Inversion Technology

“…People extract parameters related to ionosphere from ionogram, such as group path and frequency, which truly reflect the state of ionosphere, and the process of extracting the feature parameters is called recognition [2][3][4][5]. Recognition of ionograms initially relies on the manual operation performed by experienced workers.…”

“…Up to date, the public references about ionogram automatic recognition are few. Redding (1996) [9] used several steps to complete the ionogram automatic recognition. These steps include filtering noise, refining paths, model fitting and merging paths.…”