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Turkish Sensor and Detector Programs

Bros. Please all calm down. Lütfen. There are a lot of povocateurs active. "Sözüm meclisten disari " !

Ben de bir defa bile bile inadina "sözde yabanci uzman ve servis elemanlarina " LADES dedim ve Allaha Sükür ispatlarla ( amatör forensik programla) yalan dolaplarini ve SINSI psikolojik operasyonlarini belgeledim. Ama nafile.

@cabatli_53 Bro. You know for sure that a national wide GSM and Radio transmitting system can be used to detect aircrafts, if anomalies are analysed. I will work to find my old sources and publish asap.


Turkey has established own fixed GPS network for civilian and military applications thanks to land based fixed service provider and continuously corrections. Here is the service coverage areas.

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Here is the map of active signal providers
TUSAGA-Aktif


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Bros. Please all calm down. Lütfen. There are a lot of povocateurs active. "Sözüm meclisten disari " !

Ben de bir defa bile bile inadina "sözde yabanci uzman ve servis elemanlarina " LADES dedim ve Allaha Sükür ispatlarla ( amatör forensik programla) yalan dolaplarini ve SINSI psikolojik operasyonlarini belgeledim. Ama nafile.

@cabatli_53 Bro. You know for sure that a national wide GSM and Radio transmitting system can be used to detect aircrafts, if anomalies are analysed. I will work to find my old sources and publish asap.


Turkey has developed own HF radars which is able to detect the threats thousands of km away. Two of them is able to cover all Aegean and four-five of them to all Blacksea with around 120 degree horizontal scanning mode. Total liner range of an HF radar is easily exceed thousands of km. Those radars are being used to detect mostly naval activities from increadible long ranges thanks to High frequency waves' moving characteristics but They are good at detecting low flying aerial targets as well.

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@Hakan , Those GPS and HF related responses are needed to move radar projects section.
 
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Thank you much bro. I'll datamining my old archives and try to publish the tech or links how it can be used. Sagol.
Friends from Eskisehir Base told me sometime somewhere that we can watch almost to Gibraltar and boarders of Atlantic Ocean.

@cabatli_53 I will try to get in contact with Pieotr, I just saw that they have a global patent already.
They began to work on it more then 10 years ago.

Summary:


This work summarizes the author's research on radar applications of methods resulting from the assumption of signal sparsity. The term sparsity means that a signal under investigation may be modeled with a small number of components taken from a large dictionary. This property makes it possible to employ a new class of mathematical methods, recently made known as Compressive Sensing framework, for recovering the signal from the measured samples. The main feature of sparsity-based methods is that they can recover a signal uniquely from much fewer samples than methods derived from the classical sampling theory. However, this is possible only if me sparse model is adequate and if the model dictionary and measurement process conform to the specific requirements of the mathematical framework. In the present work, the author demonstrates how the mathematical theory of sparse representation and recovery may be applied to practical problems arising in radar signal processing. An overall purpose of radar signal processing is to acquire the knowledge of the radar scene from the received echo of a radio frequency signal which illuminates the investigated area. This is a problem generally belonging to the class of inverse problems, which may be ill-conditioned and ambiguous. The assumption of the sparse model of the received signal is an innovative idea that opens new possibilities of resolving ambiguities. The aim of this work was to demonstrate by means of practical examples that sparse reconstruction methods are capable of solving a series of important problems in different areas of radar signal processing. Also, more detailed research was done on these cases, including the study on sampling requirements as well as simulations of the algorithms used. The ideas and methods were verified with the use of live recorded signals wherever possible. In the examples presented in this work, sparsity of the signal model is the key assumption to enable the solution of relevant inverse problems. The application areas described here are closely related to the author's experience with existing radar systems, including those currently under research or development at the Warsaw University of Technology. They cover a wide range of radar types and processing modes, including active and passive radars as well as surveillance and imaging ones. The author proposed applications of sparsity-based methods for active radars with a noise waveform, for classical MTI radars, and for imaging radars, using either die synthetic aperture (SAR) technique with noise illumination, or the inverse synthetic aperture (ISAR) technique with passive illumination from a GSM transmitter. The ideas and methods were verified with the use of live recorded signals wherever possible. In the examples presented in this work, sparsity of the signal model is the key assumption to enable the solution of relevant inverse problems. The application areas described here are closely related to the author's experience with existing radar systems, including those currently under research or development at the Warsaw University of Technology. They cover a wide range of radar types and processing modes, including active and passive radars as well as surveillance and imaging ones. The author proposed applications of sparsity-based methods for active radars with a noise waveform, for classical MTI radars, and for imaging radars, using either die synthetic aperture (SAR) technique with noise illumination, or the inverse synthetic aperture (ISAR) technique with passive illumination from a GSM transmitter. The ideas and methods were verified with the use of live recorded signals wherever possible. In the examples presented in this work, sparsity of the signal model is the key assumption to enable the solution of relevant inverse problems. The application areas described here are closely related to the author's experience with existing radar systems, including those currently under research or development at the Warsaw University of Technology. They cover a wide range of radar types and processing modes, including active and passive radars as well as surveillance and imaging ones. The author proposed applications of sparsity-based methods for active radars with a noise waveform, for classical MTI radars, and for imaging radars, using either die synthetic aperture (SAR) technique with noise illumination, or the inverse synthetic aperture (ISAR) technique with passive illumination from a GSM transmitter. The ideas and methods were verified with the use of live recorded signals wherever possible. In the examples presented in this work, sparsity of the signal model is the key assumption to enable the solution of relevant inverse problems. The application areas described here are closely related to the author's experience with existing radar systems, including those currently under research or development at the Warsaw University of Technology. They cover a wide range of radar types and processing modes, including active and passive radars as well as surveillance and imaging ones. The author proposed applications of sparsity-based methods for active radars with a noise waveform, for classical MTI radars, and for imaging radars, using either die synthetic aperture (SAR) technique with noise illumination, or the inverse synthetic aperture (ISAR) technique with passive illumination from a GSM transmitter. The ideas and methods were verified with the use of live recorded signals wherever possible. In the examples presented in this work, sparsity of the signal model is the key assumption to enable the solution of relevant inverse problems. The application areas described here are closely related to the author's experience with existing radar systems, including those currently under research or development at the Warsaw University of Technology. They cover a wide range of radar types and processing modes, including active and passive radars as well as surveillance and imaging ones. The author proposed applications of sparsity-based methods for active radars with a noise waveform, for classical MTI radars, and for imaging radars, using either die synthetic aperture (SAR) technique with noise illumination, or the inverse synthetic aperture (ISAR) technique with passive illumination from a GSM transmitter.The ideas and methods were verified with the use of live recorded signals wherever possible. In the examples presented in this work, sparsity of the signal model is the key assumption to enable the solution of relevant inverse problems. The application areas described here are closely related to the author's experience with existing radar systems, including those currently under research or development at the Warsaw University of Technology. They cover a wide range of radar types and processing modes, including active and passive radars as well as surveillance and imaging ones. The author proposed applications of sparsity-based methods for active radars with a noise waveform, for classical MTI radars, and for imaging radars, using either die synthetic aperture (SAR) technique with noise illumination, or the inverse synthetic aperture (ISAR) technique with passive illumination from a GSM transmitter. The ideas and methods were verified with the use of live recorded signals wherever possible. In the examples presented in this work, sparsity of the signal model is the key assumption to enable the solution of relevant inverse problems. The application areas described here are closely related to the author's experience with existing radar systems, including those currently under research or development at the Warsaw University of Technology. They cover a wide range of radar types and processing modes, including active and passive radars as well as surveillance and imaging ones. The author proposed applications of sparsity-based methods for active radars with a noise waveform, for classical MTI radars, and for imaging radars, using either die synthetic aperture (SAR) technique with noise illumination, or the inverse synthetic aperture (ISAR) technique with passive illumination from a GSM transmitter. vThe ideas and methods were verified with the use of live recorded signals wherever possible. In the examples presented in this work, sparsity of the signal model is the key assumption to enable the solution of relevant inverse problems. The application areas described here are closely related to the author's experience with existing radar systems, including those currently under research or development at the Warsaw University of Technology. They cover a wide range of radar types and processing modes, including active and passive radars as well as surveillance and imaging ones. The author proposed applications of sparsity-based methods for active radars with a noise waveform, for classical MTI radars, and for imaging radars, using either die synthetic aperture (SAR) technique with noise illumination, or the inverse synthetic aperture (ISAR) technique with passive illumination from a GSM transmitter. The ideas and methods were verified with the use of live recorded signals wherever possible. In the examples presented in this work, sparsity of the signal model is the key assumption to enable the solution of relevant inverse problems. The application areas described here are closely related to the author's experience with existing radar systems, including those currently under research or development at the Warsaw University of Technology. They cover a wide range of radar types and processing modes, including active and passive radars as well as surveillance and imaging ones. The author proposed applications of sparsity-based methods for active radars with a noise waveform, for classical MTI radars, and for imaging radars, using either die synthetic aperture (SAR) technique with noise illumination, or the inverse synthetic aperture (ISAR) technique with passive illumination from a GSM transmitter. The ideas and methods were verified with the use of live recorded signals wherever possible. In the examples presented in this work, sparsity of the signal model is the key assumption to enable the solution of relevant inverse problems. The application areas described here are closely related to the author's experience with existing radar systems, including those currently under research or development at the Warsaw University of Technology. They cover a wide range of radar types and processing modes, including active and passive radars as well as surveillance and imaging ones. The author proposed applications of sparsity-based methods for active radars with a noise waveform, for classical MTI radars, and for imaging radars, using either die synthetic aperture (SAR) technique with noise illumination, or the inverse synthetic aperture (ISAR) technique with passive illumination from a GSM transmitter.The ideas and methods were verified with the use of live recorded signals wherever possible. In the examples presented in this work, sparsity of the signal model is the key assumption to enable the solution of relevant inverse problems. The application areas described here are closely related to the author's experience with existing radar systems, including those currently under research or development at the Warsaw University of Technology. They cover a wide range of radar types and processing modes, including active and passive radars as well as surveillance and imaging ones. The author proposed applications of sparsity-based methods for active radars with a noise waveform, for classical MTI radars, and for imaging radars, using either die synthetic aperture (SAR) technique with noise illumination, or the inverse synthetic aperture (ISAR) technique with passive illumination from a GSM transmitter. The ideas and methods were verified with the use of live recorded signals wherever possible. In the examples presented in this work, sparsity of the signal model is the key assumption to enable the solution of relevant inverse problems. The application areas described here are closely related to the author's experience with existing radar systems, including those currently under research or development at the Warsaw University of Technology. They cover a wide range of radar types and processing modes, including active and passive radars as well as surveillance and imaging ones. The author proposed applications of sparsity-based methods for active radars with a noise waveform, for classical MTI radars, and for imaging radars, using either die synthetic aperture (SAR) technique with noise illumination, or the inverse synthetic aperture (ISAR) technique with passive illumination from a GSM transmitter.
 
Thank you much bro. I'll datamining my old archives and try to publish the tech or links how it can be used. Sagol.
Friends from Eskisehir Base told me sometime somewhere that we can watch almost to Gibraltar and boarders of Atlantic Ocean.


Our naval engineers and civilian merchant fleet officiers know How MF/HF- DSC radio works. It uses similar principles with those devices but used for different purposes. HF/DSC radio devices enable operators to communicate with other HF devices to max. 8000-10.000km range in accordance with weather conditions and used frequencies (max 30 Mhz). Electromagnetic waves generated by antenne is reflected back to Earth thanks to Ionosphere layer, then earth reflects back same waves to ionosphere than again and again. The receiver antennes absorb the waves which is reflected by a target during Earth/Ionosphere zigzag and calculates the aprox. positions...etc. With this way, Continuously oscillating waves reach thousands of km's with being reflected by Earth/Ionosphere layers so Gibraltar is an easy target to reach for HF radar.

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LTD lazer target designator for AselPod

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ADLR-01 Air Defense Laser Range Finder
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MRLR-M Eye-Safe Laser Range Finder Module

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GZM Eye-Safe Laser Range Finder Modules
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GZM-04 Eye-Safe Laser Range Finder

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GZM-01 Eye-safe Laser Range Finder

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“PERI EYE” SERIES THERMAL CAMERAS

The PERI EYE series Thermal Cameras are compact, high performance thermal vision system, primarily designed for sighting systems that are mounted on Armoured Vehicles and Main Battle Tanks.

Peri eye MW

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Peri eye MWM
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All 3rd generation thermals...


ADIS - ASELSAN DRIVER’S VISION SYSTEM

ASELSAN's Driver's Vision System (ADIS) is a compact, high performance vision system, designed for Main Battle Tanks and other armoured vehicles. ADIS provides the driver 24-hour maneuvering capability under severe weather and harsh battlefield conditions such as fog, haze, dust, smoke, fire or camouflage. In addition, ADIS gives driver the ability to maintain continuous mission operations while providing a safe driving environment through enhanced situational awareness. ADIS is composed of thermal and CCD cameras in one compact package. This package may also be used as the rear sensor.

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ASELSAN THERMAL DRIVER’S PERISCOPE

ASELSAN Thermal Driver's Periscope is a compact, high performance vision system, designed for Main Battle Tanks and other armoured vehicles. ASELSAN Thermal Driver Periscope consists of 2 main units:

  • Thermal Camera Unit (TCU)
  • Control and Display Unit (CDU)
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ATS-40 ELECTRO OPTIC SENSOR SYSTEM

ATS-40 is a compact, high performance vision system, primarily designed for remote controlled weapon systems mounted on Armored Vehicles and Main Battle Tanks.

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ATS-60 ELECTRO OPTIC SENSOR SYSTEM

ATS-60 is a compact, high performance vision system, primarily designed for remote controlled weapon systems mounted on Armoured Vehicles and Main Battle Tanks.

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TLUS - LASER WARNING RECEIVER SYSTEM

TLUS is designed to detect almost all types of laser threats available in the world military inventory. Laser Range Finders (LRF), Laser Designators (LD) and Laser Beam Riders (LBR) threats operating on various optical bands can be detected by the system.

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NAVAL APPLICATIONS

SEAEYE - CAMGOZ
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SEAEYE – CUPRA
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SEAEYE – LEVREK
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SEAEYE – ORFOZ
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SEAEYE – YUNUS
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LIS - LASER WARNING RECEIVER SYSTEM

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PIRI (PANORAMIC INFRARED IMAGING) - IRST (INFRARED SEARCH AND TRACK SYSTEM)

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3rd generation DEPETEK-SUBMARINE PERISCOPE THERMAL CAMERA

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@Cabatli at last savunma sanayi program ASELSAN official said Air Defence Radar's range is over 600km...

Here...

TRT Haber 28.08.2015 23:25 tarihli yayını.


Bro, Aselsan's radar introductions always follow similar paths. Do you remember Aselsan Kalkan ?

Firstly, It was announced as 40km in brochure.
Then, Project head engineer Mr. Alper told us that It has a range over 80km.
If you pay attention to current figures, It is typed as 100km for Kalkan. :D
 

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