DOI: 10.15199/13.2018.2.8
The Concept of ELINT DataBase based on ERD Modelling (Koncepcja Bazy Danych ELINT powstałej w oparciu o modelowanie ERD) dr inż. Janusz DUDCZYK WB Electronics S.A., 129/133 Poznańska Street, 05-850 Ożarów Mazowiecki, Poland (e-mail:
[email protected]) phone: +48 227312755; fax: +48 227312501
Abstract This paper provides an overview of the Entity-Relationship Modelling (ERM), which is used to construct the Emitter DataBase (EDB) for current ELectronic INTelligence (ELINT) systems. The method described, delivers a data model of radar signal, called the Entity-Relationship Diagram (ERD). This model incorporates some of the important semantic information about the real radar signal and its platform, weapon system, location, antenna system, ect. A special diagrammatic technique is introduced as a tool for DataBase design, by using Barker’s notation. Also, semantic ambiguities in ERD for radar signal is analysed. The author pay special attention to the character and the meaning of the “radar signature” in DataBase, taking into consideration the difficulties that appear during the process of the parameter selection. Special ERD of radars, presented in this paper, can be used in real time or non-real time on any PC computer with portable HDD containing the signals collected earlier. Such approach is very convenient to operators’ training as it gives them an opportunity to meet rare radar signals and reduces the cost of Electronic Warfare (EW) exercises. Keywords: Emitter DataBase, ELINT System, Entity-Relationship Diagram, Electronic Warfare
Streszczenie Niniejszy artykuł przedstawia metodę Modelowania Związków Encji (MZE), która została wykorzystana do budowy Bazy Danych Emiterów (BDE) sygnałów radarowych, mającej zastosowanie we współczesnych systemach rozpoznania elektronicznego ELINT. Zaprezentowana metoda dostarcza model danych sygnału radarowego w postaci Diagramu Związków Encji (DZE). Model ten, zawiera ważne informacje semantyczne o rzeczywistym sygnale radarowym, jego platformie, systemie uzbrojenia, lokalizacji, systemie antenowym, itd. Baza Danych Emiterów została zaprojektowana przy użyciu sformalizowanego zapisu graficznego w notacji Barkera. Również w procesie projektowania zostały poddane analizie wieloznaczności semantyczne sygnału radarowego w aspekcie powstałego DZE. Autor pragnie zwrócić szczególną uwagę na charakter i znaczenie „metryki radaru” w bazie danych, biorąc pod uwagę trudności pojawiające się podczas procesu doboru parametrów opisujących ww. metrykę. Diagram Związków Encji sygnałów radarowych przedstawiony w niniejszym artykule, może być używany w czasie rzeczywistym na dowolnym sprzęcie komputerowy klasy PC z przenośnym dyskiem twardym zawierającym zarejestrowane wcześniej sygnały radarowe. Takie podejście jest bardzo wygodne dla analityków oraz operatorów systemów ELINT i umożliwia przetwarzanie rzadko spotykanych sygnałów radarowych przy jednoczesnej minimalizacji kosztów ćwiczeń w zakresie Walki Elektronicznej (WE). Słowa kluczowe: Baza Danych Emiterów, System ELINT, Diagram Związków Encji, Walka Elektroniczna
The present ELectronic INTelligence system (ELINT) must be able to fulfill specific requirements [1]. In this case, ELINT system ought to realize the fusion on data and include an Emitter DataBase (EDB) which was designed correctly [2]. Database systems and database design technology have undergone significant evolution in recent years [3]. The process of designing the optimal structure of emitter DataBase for radars is a very complicated and sophisticated task. The main problem that appears during the process of constructing the DataBase is the difficulty in selecting the features correctly. The relationship modeling is an essential element in forming the electronic intelligence system. A data model, called the Entity-Relationship incorporates some of the important semantic information about the real world [4, 5]. During the process of designing the emitter DataBase, the engineer-designer should consider the following aspects, i.e.: proper selection and correlation of the information with the determined type of data, possibility of data actualization and modification (dynamic structure of the data), depriving of data redundancy, possibility of data impor-
ting and exporting to/from the emitter DataBase, co-operation the DataBase with other applications and an easy access to the information during the process of data finding, integrity of information in EDB, safety of DB system and utilizing artificial intelligence, statistics gathering, monitoring and alerting, knowledge-based systems, expert systems, and workflow management during the process of DataBase designing [6–9]. The Emitter DataBase should be implemented by the special software for DataBase, which ought to fulfill the following requirements, i.e.: screen visualization of the results of radar signals identification, adding new patterns of signals or updating the existing DataBase and association of tactical platform parameters with appropriate radar pattern signals. Also, detecting and removing errors is an essential factor during the process of DB projecting. Errors are the reason for disagreement. The “data integrity” means the “correct state” of the EDB and refers to maintaining and assuring the accuracy and consistency of data over its entire life-cycle [10, 11].
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The Structure of Radar Metrics in EDB The success of modern Electronic Warfare (EW) depends on a DataBase which is designed correctly. The EDB should include the patterns of radar devices, the technical characteristics of electromagnetic sources and the permanent possibility of data modification. According to available bibliography concerning the subject matter, the EDB ought to possess approximately several thousands of emitters patterns. All information contained in DataBase can be divided into logical, numerical, descriptive and graphic groups. As a result of the measure procedure of a radar signal it is possible to present each of the analysed signal features N in the form of a numerical value. Thus, a formal description of a radar is a set of N numbers x = (x1, x2,...,xN), called the object image. In reality the object image can be not only a set of numbers but also collections of logical expressions and collections describing its structure. The exact description of a source emission is significant as far as the proper construction register of a radar in the database is concerned. The designer of a DataBase should take into account measurable and unmeasurable features, which means all accessible information on emission’s source. The measurable feature is a result of measurements and calculations. The unmeasurable feature can be expressed by the chain of words or logical expressions. All information classified in this way should be contained in radar signature–radar metrics. Continuously variable data can accept facultative values from selected section of real numbers’ axis. The binary data of the first kind accepts binary values such as “0” or “1”. These features are expressed by qualitative character of occurrence or lack of certain properties. The third group of information referred to as “the binary data of the second kind” is characterized by not-derivative elements of an object’s structure, expressed by a chain of words or
characters. An example of radar’s object image is expressed in the form of Radar Vector Parameters (RVP) by equation (1), where means the continuously variable data, is the binary data of the first kind and is the binary data of the second kind. Indexes mean respectively, the quantity of the continuously variable data and the quantity of the binary data of first and second kind and denotes transposition. A precise description of the radar signal parameters is presented in [12, 13]. T
RVP j = [ x j1 , x j 2 ,..., x jN , y j1 , y j 2 ,..., y jM , z j1 , z j 2 ,..., z jP ]
(1)
The classification of the radar information presented above, makes it possible to project accurately a radar signature in the DataBase. This approach offers the possibility of creating the DataBase emitter in an optimal way without redundancy features. At the same time, this “data partition” permits to use “the knowledge-based approach” during the process of constructing the DataBase [14]. All information included in the DataBase is called the radar signature. This “metrics” illustrated in Fig. 1, includes all accessible information about radars’ emissions for example, the principal parameters of radar signals and their range of changes, the technical characteristics, catalogue data, and many others. The set of parameters in DataBase has been divided into the subsets, which are represented by entities. Some of them are illustrated in Fig. 2 by ERD.
Entity Relationship Diagram Concept of EDB An Entity Relationship Diagram is a logical diagram representing the database structure using the relational model. There are different notations of ERDs, for the following notes
RADAR METRICS APPLIED TO EDB EMITTER_RADIATE D POWER (ERP)
ANTENNA
PULSE_GROUP_ PATTERN
MODE
SP_MOST_OBSERVE D
PD_MODULATION
RF_MOST_OBSERV ED
RF_BEAM_VALUES
PD_PMOD
RF_CHANNELS VALUE
RF_AGILITY_OOK
PD_FMOD
RADIATED_EMISSI ON PARAMETERS
EMITTER
PRI_DWELL
WEAPON_ ALTERNATE
CRYSTAL_RF
PRI_SLIDING
PLATFORM_ LOCATION
PRI_STAGGER
PRF_PRI_MOST_ OBSERVED VALUE
SCAN
PRI_PRF
FRACTAL_FEATUR E
SCAN_RASTER
PRI_JITTER
SEI_FEATURE
Fig. 1. The structure of radar metrics in EDB for ELINT System Rys. 1. Struktura metryki radaru w bazie danych emiterów systemu ELINT
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RF_CHANNELS_ VALUES # Crystal_Freq * Number_Of_Channels * Channel_Step_Min * Channel_Step_Max * Channel_No * RF_Min
MODE # ID_EMT * MC * MP * FC1 * FC2 * SN * SD * C Date include
defined equipped REP with # ID_EMT * EFV_Structure characterize * C_Date WEAPON_ ALTERNATE # ID_EMT * Name_Weapon * Alternate_Weapon
EMITTER # ID_EMT * NSN * Code_Type * EPM_Features equipped * EN with 0 Nick 0 Image connected 0 UC
correspond
characterize ć CRYSTAL_RF # ID_EMT * Crystal_Freq defined * Crystal_Count_Down * RF_Min concerns * RF_Max * RF_Mod_Type_Code * Polarization_Type 0 UC
RF_AGILITY_OOK # Crystal_Freq * RF_Agility_Type * RF_Agility_Rate * RF_Shift_Min defined * RF_Shift_Max include * Dwell_Time_On_RF * On_Time_Min * On_Time_Max * Of_Time_Min * Of_Time_Max
defined ANTENNA # ID_EMT
include
* Antenna_Type * Elevation * Azimuth * BW_Horizontal * BW_Vertical
include
SCAN # Antenna_Type * SP_Min * SP_Max defined * SR_Min * SR_Max * Scan_Type 0 UC
SCAN_RASTER # Scan_Type * Number_Of_Bars * Number_Of_Levels * Number_Of_Lobes * Raster_Time * Raster_Width_AZ * Raster_Width_EL
Fig. 2. A sample part of ERD of Emitter DataBase using Barker’s notation Rys. 2. Przykład fragmentu diagramu ERD Bazy Danych Emiterów w notacji Barkera
Barker’s notation shall be adopted. Barker’s notation refers to the ERD notation developed by Richard Barker [15]. This notation was and is still used by the Oracle CASE modelling tools. Entity modelling is a particular formal technique for the representation of conceptual models; it represents Entity Framework (for example: Regular Entity such as MODE or REP, Weak Entity such as EMITTER or Hierarchical Entity such as SCAN) as labelled boxes and relationships as annotated connections between boxes. Generally, ERDs make use of three concepts, i.e.: entity, attribute and relationship. An entity is an object that is important to include. An attribute is a property of an entity which describes the characteristics of a particular entity instance. An attribute can be of three types: unique identifier, mandatory attribute and optional attribute. A relationship links two or more entity instances together and can be mandatory or optional. When drawing an Entity, Attribute and Relationship using Barker’s notation some rules need to be respected, see [15]. The relational Emitter DataBase of radars is designed according to the three schema approaches to software engineering: Conceptual Data Model (CDM) [16], Logical Data Model (LDM) and Physical Data Model (PDM). A CDM is the highest level model. This model normally defines master reference data entities that are commonly used by the organization. The purpose of the CDM is then to establish structural metadata commonality for the master data entities between the set of LDM. A LDM
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contains more details than the CDM. Additionally, master data entities, operational and transactional data entities are now defined. The details of each data entity are developed and the entity relationships between these data entities are established. However, the logical ER model is developed independently of the technology into which it will be implemented. A PDM is normally developed to be instantiated as a database. Therefore, each physical ER model must contain enough number of details to produce a database. The physical model is normally engineered forward to instantiate the structural metadata into a database management system as relational database objects such as tables, indexes and database constraints such as a foreign key or a commonality constraint. It is worth pointing out that the process of DB design based on the ERM should be defined accurately, i.e.: in the case of Barker’s notation. Every entity must be identified univocally. An entity should be described by its attributes. Also both perspectives of a relationship must be labelled. The ERD is the first stage of DataBase design. An entity is illustrated by a frame. An entity’s name is located in the middle of the frame for example, EMITTER or WEAPON_ALTERNATE. The line connecting two entities’ frames together illustrates the relationship between the entities. Every relationship must be defined by the degree of relationship (it can be single or plural), the optionality (optionality defines the type of connection: mandatory or optional) and the name of connection (relationship must be labelled), see Fig. 2. The
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concept of ERD creation should take into account “radar signature” in the DataBase. The “radar signature” in DataBase includes all available data on radar signals. The main problem is to determine what information should be stored in the DataBase and correlate it with data types. In this case every entity should have a substitute in previously prepared “radar signature-metrics” (see Fig. 1).
The Evaluation Process of EDB Identification The author of this article put special emphasis on drawing up radar metrics and implementation of these metrics in the DataBase on the basis of the diagram of entity relationships. It is not trivial to complete such a task because of for instance, problems which appear during the selection of specific parameters of emission source (in this case- the radar). Moreover, what has to be mentioned is the fact that when there is a need to identify radar copies of the same type, Specific Emitter Identification (SEI) methods ought to be used, which should be also taken into account in the ELINT system [12, 13, 17]. The DataBase in this case ought to use the received information from the SEI process effectively and on such a base it should create distinctive records which describe explicitly particular emission source copies. The final process of radar identification is based (for example) on hierarchical clustering which is implemented during the EDB construction process [13]. This implemented algorithm is based on agglomerative strategy [13, 18, 19].
Conclusion Designing an optimal structure of ELINT system’s DataBase is a very sophisticated task. This paper described the requirements, which should be fulfilled by an engineer-designer during the DataBase projecting. The EDB shown here was designed by using the ERM. The process of final radar identification, based on hierarchical clustering with agglomerative strategy, was implemented during the DataBase creation. The recording data in the form of RVPs and results of their analysis help us to extract some facts to construct the knowledge base and design the expert systems in the last stage of radar identification. The ERD depriving DataBase of redundancy features, can be used in the ELINT system or another military application [1, 6]. Furthermore, the development of these techniques provides a powerful way ahead for their application to other related signal processing areas such as image processing and expert systems. The next step should be applying the automatic defining mechanism of distance classifier and various distance metrics. The EDB mentioned here is a good solution in the process of radars identification. This problem will be still examined by the author of this article, in the presented EDB for ELINT system.
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