US20090091490A1 - Method and system for radar tracking of moving target from moving station - Google Patents
Method and system for radar tracking of moving target from moving station Download PDFInfo
- Publication number
- US20090091490A1 US20090091490A1 US11/986,531 US98653107A US2009091490A1 US 20090091490 A1 US20090091490 A1 US 20090091490A1 US 98653107 A US98653107 A US 98653107A US 2009091490 A1 US2009091490 A1 US 2009091490A1
- Authority
- US
- United States
- Prior art keywords
- radar
- axis
- moving target
- gaussian
- array
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
Images
Classifications
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S7/00—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00
- G01S7/02—Details of systems according to groups G01S13/00, G01S15/00, G01S17/00 of systems according to group G01S13/00
- G01S7/28—Details of pulse systems
- G01S7/285—Receivers
- G01S7/295—Means for transforming co-ordinates or for evaluating data, e.g. using computers
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/06—Systems determining position data of a target
- G01S13/46—Indirect determination of position data
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/66—Radar-tracking systems; Analogous systems
- G01S13/72—Radar-tracking systems; Analogous systems for two-dimensional tracking, e.g. combination of angle and range tracking, track-while-scan radar
- G01S13/723—Radar-tracking systems; Analogous systems for two-dimensional tracking, e.g. combination of angle and range tracking, track-while-scan radar by using numerical data
-
- G—PHYSICS
- G01—MEASURING; TESTING
- G01S—RADIO DIRECTION-FINDING; RADIO NAVIGATION; DETERMINING DISTANCE OR VELOCITY BY USE OF RADIO WAVES; LOCATING OR PRESENCE-DETECTING BY USE OF THE REFLECTION OR RERADIATION OF RADIO WAVES; ANALOGOUS ARRANGEMENTS USING OTHER WAVES
- G01S13/00—Systems using the reflection or reradiation of radio waves, e.g. radar systems; Analogous systems using reflection or reradiation of waves whose nature or wavelength is irrelevant or unspecified
- G01S13/02—Systems using reflection of radio waves, e.g. primary radar systems; Analogous systems
- G01S13/06—Systems determining position data of a target
- G01S13/46—Indirect determination of position data
- G01S2013/466—Indirect determination of position data by Trilateration, i.e. two antennas or two sensors determine separately the distance to a target, whereby with the knowledge of the baseline length, i.e. the distance between the antennas or sensors, the position data of the target is determined
Definitions
- This invention relates to radar technology, and more particularly, to a method and system for radar tracking of a moving target (such as an air-to-air missile) from a moving station (such as a jetfighter) with improved accuracy and performance.
- a moving target such as an air-to-air missile
- a moving station such as a jetfighter
- a radar system is a radio-based surveilance system that uses electromagnetic waves to identify the range, altitude, direction, or speed of moving or fixed objects such as aircraft, ships, and motor vehicles.
- a radar system is capabale of emitting a beam of radio wave toward the area under surveilance, and if a target exists in that area, the emitted radio wave will be reflected back. The reflected radio wave is then received by the radar system and analyzed to determine the position, speed, and acceleration of the target.
- Radar systems are categorized into ground-based type and airborne type.
- the airborne-type radar systems are installed on airplanes such as jetfighters for detecting air-to-air missiles or nearby airplanes.
- the detected radar data represents the relative position, relative speed, and relative acceleration of the target.
- the invention comprises: (M1) emitting a radar signal beam; (M2) sensing an echo of the radar signal beam from a moving target and producing a raw set of radar data about the moving target, including range, velocity, and acceleration; (M3) performing S/N (signal-to-noise ratio) enhancement of each raw set of radar data; (M4) performing trilateration on the S/N-enhanced sets of radar data in reference to a predefined 3-dimenional coordinate system having a first axis, a second axis, and a third axis to obtain three axis-oriented sets of radar data respectively in reference to the first axis, the second axis, and the third axis of the 3-dimenional coordinate system; (M5) performing S/N enhancement on the trilateration-resulted sets of radar data; and (M6) a radar data presentation module, which is capable of presenting the S/N-enhanced sets of radar data produced by the second Gaussian-noise filter
- the moving object radar tracking system comprises: (A) a radar signal emitter; (B) a radar signal sensor array including an array of N radar signal sensors that are preferably each implemented with a hybrid FSK/LFM sensors; (C) a first Gaussian-noise filter array including an array of N Gaussian-noise filters that are preferably implemented with one-stage linear Kalman filters; (D) a trilateration module; (E) a second Gaussian-noise filter array, which includes at least 3 Gaussian-noise filters that are preferably implemented with an array of one-stage linear Kalman filters; and (F) a radar data presentation module.
- the method and system for tracking moving target from moving station is characterized by the use of a hybrid FSK/LFM (Frequency Shift Keying & Linear Frequency Modulation) scheme for acquiring a collection of raw radar data, a first Gaussian-noise filter array of one-stage linear Kalman filters for S/N-enhancement of the raw radar data, a trilateration module, and a second Gaussian-noise filter array of one-stage linear Kalman filters for S/N-enhancement of the trilateration-resulted radar data.
- FSK/LFM Frequency Shift Keying & Linear Frequency Modulation
- FIG. 1 is a schematic diagram showing the application of the moving target radar tracking system according to the invention
- FIG. 2 is a schematic diagram showing the internal architecture of the moving target radar tracking system according to the invention.
- FIG. 3A is a graph showing the characteristic plot of frequency variation of an LFM signal using a conventional FSK/LFM technique.
- FIG. 3B is a graph showing the characteristic plot of frequency variation of a pair of LFM signals using a modified FSK/LFM technique in accordance with the invention.
- FIG. 1 is a schematic diagram showing an application example of the moving target radar tracking system according to the invention (which is here encapsulated in a box indicated by the reference numeral 100 ).
- the moving target radar tracking system of the invention 100 is designed for installation on a moving station, such as a jetfighter 10 , for the jetfighter 10 to detect the position and motion of a moving target, such as an air-to-air missile (AAM) 20 that is in constant changes of position and motion relative to the jetfighter 10 .
- AAM air-to-air missile
- the moving object radar tracking system of the invention 100 will respond to this condition by indicating the position, speed, and acceleration of the AAM 20 to the pilot of the moving target radar tracking system of the invention 100 .
- the moving target radar tracking system of the invention 100 comprises: (A) a radar signal emitter 110 ; (B) a radar signal sensor array 120 , which includes an array of N radar signal sensors that are preferably each implemented with a hybrid FSK/LFM sensors; (C) a first Gaussian-noise filter array 130 , which includes N Gaussian-noise filters that are preferably each implemented with a one-stage linear Kalman filter; (D) a trilateration module 140 ; (E) a second Gaussian-noise filter array 150 , which includes at least 3 Gaussian-noise filters 151 , 152 , 153 , that are preferably implemented with an array of one-stage linear Kalman filters; and (F) a radar data presentation module 160 .
- the respective functions of the constituent components of the moving target radar tracking system of the invention 100 are described in details in the following.
- the radar signal emitter 110 is used for emitting a beam of radar signal into the space under surveillance by the jetfighter 10 . If an AAM 20 is in the proximity of the jetfighter 10 , the radar signal beam will hit the AAM 20 and reflect as an echoed radar signal back to the jetfighter 10 .
- the radar signal sensor array 120 includes an array of N radar signal sensors that are preferably implemented with a plurality of hybrid FSK/LFM sensors, each of which is based on a combination of the FSK (Frequency Shift Keying) and the LFM (Linear Frequency Modulation) techniques for extracting a set of position-motion data about the AAM 20 , including the range, radial velocity, and radial acceleration of the AAM 20 based on the echoed radar signal.
- the number N can be 2, 3, or more.
- the N hybrid FSK/LFM sensors in the radar signal sensor array 120 are respectively used for the sampling of a raw set of position-motion data, represented by ⁇ r 1 , v 1 , a 1 ⁇ , ⁇ r 2 , v 2 , a 2 ⁇ , . . . , and ⁇ r N , v N , a N ⁇ , respectively.
- a raw set of position-motion data represented by ⁇ r 1 , v 1 , a 1 ⁇ , ⁇ r 2 , v 2 , a 2 ⁇ , . . . , and ⁇ r N , v N , a N ⁇ , respectively.
- the hybrid FSK/LFM sensors in the radar signal sensor array 120 is capable of additionally acquiring the acceleration of the AAM 20 , rather than just the range and velocity of the AAM 20 by this prior art.
- Each hybrid FSK/LFM sensor in the radar signal sensor array 120 is designed to compute for the range r, radial velocity v, and radial acceleration a of the AAM 20 based on a modified FSK/LFM technique as described below.
- FIG. 3A a graph showing the characteristic plot of the frequency variation of an LFM signal using the conventional FSK/LFM technique (in this graph, B sweep represents bandwidth and T LFM represents dwell time); whereas FIG. 3B is a graph showing the characteristic plot of the frequency variation of a pair of LFM signals utilized by the invention.
- J _ [ 2 ⁇ s 2 ⁇ f A ⁇ ( t ) 0 2 ⁇ s 2 ⁇ [ f B ⁇ ( t ) + s ⁇ ⁇ ] 2 ⁇ [ f B ⁇ ( t ) ⁇ ⁇ + s ⁇ ⁇ 2 ⁇ / ⁇ 2 ] 4 ⁇ f shif ⁇ t 4 ⁇ f B ⁇ ( t ) ⁇ ⁇ 2 ⁇ f B ⁇ ( t ) ⁇ ⁇ 2 ]
- the first Gaussian-noise filter array 130 includes N Gaussian-noise filters which are preferably implemented with an array of N one-stage linear Kalman filters, each being coupled to one of the N hybrid FSK/LFM sensors in the radar signal sensor array 120 .
- N one-stage linear Kalman filters are capable of reducing the Gaussian-noise in the output datasets ⁇ r 1 , v 1 , a 1 ⁇ , ⁇ r 2 , v 2 , a 2 ⁇ , . . . , and ⁇ r N , v N , a N ⁇ from the N hybrid FSK/LFM sensors in the radar signal sensor array 120 .
- These N one-stage linear Kalman filters are based on a conventional Gaussian-noise filtering technology, so detailed description thereof will not be given in this specification.
- the None-stage linear Kalman filters in the first Gaussian-noise filter array 130 are used in combination to produce a collection of N S/N-enhanced sets of position-motion data about the AAM 20 , which are represented by ⁇ circumflex over (r) ⁇ 1 , ⁇ circumflex over (v) ⁇ 1 , â 1 ⁇ , ⁇ circumflex over (r) ⁇ 2 , ⁇ circumflex over (v) ⁇ 2 , â 2 ⁇ , . . . , and ⁇ circumflex over (r) ⁇ N , ⁇ circumflex over (v) ⁇ N , â N ⁇ , respectively.
- the trilateration module 140 is used for processing the N S/N-enhanced datasets ⁇ circumflex over (r) ⁇ 1 , ⁇ circumflex over (v) ⁇ 1 , â 1 ⁇ , ⁇ circumflex over (r) ⁇ 2 , ⁇ circumflex over (v) ⁇ 2 , â 2 ⁇ , . . .
- ⁇ circumflex over (r) ⁇ 2 , ⁇ circumflex over (v) ⁇ 2 , â 2 ⁇ from the first Gaussian-noise filter array 130 in reference to a predefined 3-dimenional (3-D) coordinate system, preferably a 3-D rectangular coordinate system having an x-axis, a y-axis, and a z-axis, to thereby obtain a collection of 3 axis-oriented sets of position-motion data respectively in reference to the x-axis, the y-axis, and the z-axis of the 3-D rectangular coordinate system.
- 3-D coordinate system preferably a 3-D rectangular coordinate system having an x-axis, a y-axis, and a z-axis
- the trilateration process yields a set of position data ⁇ circumflex over (x) ⁇ , ⁇ , ⁇ circumflex over (z) ⁇ , a set of velocity data ⁇ circumflex over (v) ⁇ x , ⁇ circumflex over (v) ⁇ y , ⁇ circumflex over (v) ⁇ z ⁇ , and a set of acceleration data ⁇ â x , â y , â z ⁇ in accordance with the following equations (A1), (A2), and (A3):
- the 3 hybrid FSK/LFM sensors in the radar signal sensor array 120 can be used to respectively acquire three samples of range data ⁇ circumflex over (r) ⁇ 1 , ⁇ circumflex over (r) ⁇ 2 , ⁇ circumflex over (r) ⁇ 3 ⁇ , which are mathematically expressed as follows:
- ⁇ circumflex over (r) ⁇ 1 2 ( ⁇ circumflex over (x) ⁇ x 1 ) 2 + ⁇ 2 + ⁇ circumflex over (z) ⁇ 2 (1)
- ⁇ circumflex over (r) ⁇ 2 2 ( ⁇ circumflex over (x) ⁇ x 2 ) 2 + ⁇ 2 + ⁇ circumflex over (z) ⁇ 2 (2)
- ⁇ circumflex over (r) ⁇ 3 2 ⁇ circumflex over (x) ⁇ 2 +( ⁇ y 3 ) 2 +( ⁇ circumflex over (z) ⁇ z 3 ) 2 (3)
- x ⁇ x 1 2 - x 2 2 - r ⁇ 1 2 + r ⁇ 2 2 2 ⁇ ( x 1 - x 2 )
- y ⁇ - - p 2 + p 2 2 - 4 ⁇ p 1 ⁇ p 3 2 ⁇ p 1
- p 3 p 4 2 - r ⁇ 2 2 + ( x ⁇ - x 2 ) 2
- p 4 r 2 2 - ( x ⁇ - x 2 ) 2 - r ⁇ 3 2 + x ⁇ 2 + y 3 2 + z 3 2 2 ⁇ z 3
- ⁇ circumflex over (v) ⁇ 1 , ⁇ circumflex over (v) ⁇ 2 , ⁇ circumflex over (v) ⁇ 3 ⁇ is mathematically related to ⁇ circumflex over (v) ⁇ x , ⁇ circumflex over (v) ⁇ y , ⁇ circumflex over (v) ⁇ z ⁇ as follows:
- ⁇ â x , â y , â z ⁇ is related to ⁇ â 1 , â 2 , â 3 ⁇ as follows:
- the second Gaussian-noise filter array 150 includes an array of at least 3 Gaussian-noise filters which are preferably implemented with 3 one-stage linear Kalman filters including a first Gaussian-noise filter 151 , a second Gaussian-noise filter 152 , and a third Gaussian-noise filter 153 .
- the first Gaussian-noise filter 151 is used for S/N enhancement of the x-axis oriented dataset ⁇ circumflex over (x) ⁇ , ⁇ circumflex over (v) ⁇ z , â x ⁇ to thereby obtain a noise-reduced dataset, here represented by ⁇ tilde over (x) ⁇ , ⁇ tilde over (v) ⁇ x , ⁇ x ⁇ ;
- the second Gaussian-noise filter 152 is used for S/N enhancement of the y-axis oriented set of position-motion data ⁇ , ⁇ circumflex over (v) ⁇ y , â y ⁇ to thereby obtain a noise-reduced dataset, here represented by ⁇ tilde over (y) ⁇ , ⁇ tilde over (v) ⁇ y , ⁇ y ⁇ ;
- the third Gaussian-noise filter 153 is used for S/N enhancement of the z-axis oriented set of position-motion data ⁇ circ
- the radar presentation module 160 is used to present the output S/N-enhanced datasets ⁇ tilde over (x) ⁇ , ⁇ tilde over (v) ⁇ x , ⁇ x ⁇ , ⁇ tilde over (y) ⁇ , ⁇ tilde over (v) ⁇ y , ⁇ y ⁇ , ⁇ tilde over (z) ⁇ , ⁇ tilde over (v) ⁇ z , ⁇ z ⁇ in human-coginzable data format for the purpose of informing the pilot of the jetfighter 10 of the position, speed, and acceleration of the threatening AAM 20.
- the output datasets ⁇ tilde over (x) ⁇ , ⁇ tilde over (v) ⁇ x , ⁇ x ⁇ , ⁇ tilde over (y) ⁇ , ⁇ tilde over (v) ⁇ y , ⁇ y ⁇ , ⁇ tilde over (z) ⁇ , ⁇ tilde over (v) ⁇ z , ⁇ z ⁇ from the second Gaussian-noise filter array 150 are rearranged into ⁇ tilde over (x) ⁇ , ⁇ tilde over (y) ⁇ , ⁇ tilde over (z) ⁇ for position, ⁇ tilde over (v) ⁇ x , ⁇ tilde over (v) ⁇ y , ⁇ tilde over (v) ⁇ z ⁇ for velocity, and ⁇ x , ⁇ y , ⁇ z ⁇ for acceleration.
- These datasets are then used to drive, for example, a monitor screen (not shown) for visually presenting the position, speed, and acceleration of the
- the moving target radar tracking system of the invention 100 is installed on a jetfighter 10 and, during flight of the jetfighter 10 , an AAM 20 is launched against the jetfighter 10 .
- the radar signal sensor array 110 is activated to emit a beam of radar signal into the space under surveillance by the jetfighter 10 .
- the emitted radar signal beam hits the AAM 20 , it will reflect as an echoed radar signal back to the jetfighter 10 and which is sampled by the N hybrid FSK/LFM sensors in the radar signal sensor array 120 to produce a collection of N datasets ⁇ r 1 , v 1 , a 1 ⁇ , ⁇ r 2 , v 2 , a 2 ⁇ , . . . and ⁇ r N , v N , a N ⁇ .
- these N datasets ⁇ r 1 , v 1 , a 1 ⁇ , ⁇ r 2 , v 2 , a 2 ⁇ , . . . , and ⁇ r N , v N , a N ⁇ are transferred to the first Gaussian-noise filter array 130 , which includes an array of N one-stage linear Kalman filters, for S/N enhancement before undergoing trilateration.
- the trilateration process yields a set of position data ⁇ circumflex over (x) ⁇ , ⁇ , ⁇ circumflex over (z) ⁇ , a set of velocity data ⁇ circumflex over (v) ⁇ x , ⁇ circumflex over (v) ⁇ y , ⁇ circumflex over (v) ⁇ z ⁇ , and a set of acceleration data ⁇ â x , â y , â z ⁇ .
- the first Gaussian-noise filter 151 is used for S/N enhancement of the x-axis oriented dataset ⁇ circumflex over (x) ⁇ , ⁇ circumflex over (v) ⁇ x , â x ⁇ ;
- the second Gaussian-noise filter 152 is used for S/N enhancement of the y-axis oriented dataset ⁇ , ⁇ circumflex over (v) ⁇ y , â y ⁇ ;
- the third Gaussian-noise filter 153 is used for S/N enhancement of the z-axis oriented dataset ⁇ circumflex over (z) ⁇ , ⁇ circumflex over (v) ⁇ z , â z ⁇ .
- the resulted S/N-enhanced datasets are represented by ⁇ tilde over (x) ⁇ , ⁇ tilde over (v) ⁇ x , ⁇ x ⁇ , ⁇ tilde over (y) ⁇ , ⁇ tilde over (v) ⁇ y , ⁇ y ⁇ , and ⁇ tilde over (z) ⁇ , ⁇ tilde over (v) ⁇ z , ⁇ z ⁇ , respectively.
- the invention provides a method and system for radar tracking of a moving target (such as an air-to-air missile) from a moving station (such as a jetfighter) with improved accuracy and performance.
- the proposed method and system is characterized by the use of a hybrid FSK/LFM scheme for acquiring a collection of raw radar data, a first Gaussian-noise filter array of one-stage linear Kalman filters for S/N-enhancement of the raw radar data, a trilateration module, and a second Gaussian-noise filter array of one-stage linear Kalman filters for S/N-enhancement of the trilateration-resulted radar data.
Landscapes
- Engineering & Computer Science (AREA)
- Radar, Positioning & Navigation (AREA)
- Remote Sensing (AREA)
- Computer Networks & Wireless Communication (AREA)
- Physics & Mathematics (AREA)
- General Physics & Mathematics (AREA)
- Radar Systems Or Details Thereof (AREA)
Abstract
Description
- 1. Field of the Invention
- This invention relates to radar technology, and more particularly, to a method and system for radar tracking of a moving target (such as an air-to-air missile) from a moving station (such as a jetfighter) with improved accuracy and performance.
- 2. Description of Related Art
- A radar system is a radio-based surveilance system that uses electromagnetic waves to identify the range, altitude, direction, or speed of moving or fixed objects such as aircraft, ships, and motor vehicles. In operation, a radar system is capabale of emitting a beam of radio wave toward the area under surveilance, and if a target exists in that area, the emitted radio wave will be reflected back. The reflected radio wave is then received by the radar system and analyzed to determine the position, speed, and acceleration of the target.
- Radar systems are categorized into ground-based type and airborne type. The airborne-type radar systems are installed on airplanes such as jetfighters for detecting air-to-air missiles or nearby airplanes. In this type of application, since the radar system and the target are both moving, the detected radar data represents the relative position, relative speed, and relative acceleration of the target.
- Many research efforts have been conducted on airborne radar systems intended for air-to-air missile detections. For example, the technical paper “WAVEFORM DESIGN PRINCIPLES FOR AUTOMOTIVE RADAR SYSTEMS” authored by H. Rohling and M. M. Meinecke, IEEE Radar, pp. 1-4. October 2001, proposes a radar system that utilizes a hybrid FSK/LFM (Frequency Shift Keying & Linear Frequency Modulation) technique for detection of relative distance and relative speed between the radar system and the target.
- One drawback to the aforementioned radar system, however, is that the hybrid FSK/LFM sensor is only capable of detecting the range and speed of the target, and incapable of detecting the acceleration.
- Moreover, many conventional radar systems utilize trilateration to obtain the range, velocity, and acceleration of the target from a collection of raw radar data. One drawback to the trilateration process, however, is that it would undesirably degrade the S/N (signal-to-nose ratio) of the original radar data.
- It is therefore an objective of this invention to provide a new radar method and system that utilizes a new and modified FSK/LFM technique capable of detecting the acceleration of the target in addition to the target's range and speed.
- It is another objective of this invention to provide a new radar method and system that can provide enhanced S/N ratio of the detected data for improved accuracy of target tracking.
- Defined as a method, the invention comprises: (M1) emitting a radar signal beam; (M2) sensing an echo of the radar signal beam from a moving target and producing a raw set of radar data about the moving target, including range, velocity, and acceleration; (M3) performing S/N (signal-to-noise ratio) enhancement of each raw set of radar data; (M4) performing trilateration on the S/N-enhanced sets of radar data in reference to a predefined 3-dimenional coordinate system having a first axis, a second axis, and a third axis to obtain three axis-oriented sets of radar data respectively in reference to the first axis, the second axis, and the third axis of the 3-dimenional coordinate system; (M5) performing S/N enhancement on the trilateration-resulted sets of radar data; and (M6) a radar data presentation module, which is capable of presenting the S/N-enhanced sets of radar data produced by the second Gaussian-noise filter array in a human-cognizable data form.
- The moving object radar tracking system according to the invention comprises: (A) a radar signal emitter; (B) a radar signal sensor array including an array of N radar signal sensors that are preferably each implemented with a hybrid FSK/LFM sensors; (C) a first Gaussian-noise filter array including an array of N Gaussian-noise filters that are preferably implemented with one-stage linear Kalman filters; (D) a trilateration module; (E) a second Gaussian-noise filter array, which includes at least 3 Gaussian-noise filters that are preferably implemented with an array of one-stage linear Kalman filters; and (F) a radar data presentation module.
- The method and system for tracking moving target from moving station according to the invention is characterized by the use of a hybrid FSK/LFM (Frequency Shift Keying & Linear Frequency Modulation) scheme for acquiring a collection of raw radar data, a first Gaussian-noise filter array of one-stage linear Kalman filters for S/N-enhancement of the raw radar data, a trilateration module, and a second Gaussian-noise filter array of one-stage linear Kalman filters for S/N-enhancement of the trilateration-resulted radar data. These features allow the radar tracking of moving objects to be more fast and accurate.
- The invention can be more fully understood by reading the following detailed description of the preferred embodiments, with reference made to the accompanying drawings, wherein:
-
FIG. 1 is a schematic diagram showing the application of the moving target radar tracking system according to the invention; -
FIG. 2 is a schematic diagram showing the internal architecture of the moving target radar tracking system according to the invention; -
FIG. 3A is a graph showing the characteristic plot of frequency variation of an LFM signal using a conventional FSK/LFM technique; and -
FIG. 3B is a graph showing the characteristic plot of frequency variation of a pair of LFM signals using a modified FSK/LFM technique in accordance with the invention. - The moving target radar tracking system of the invention according to the invention is disclosed in full details by way of preferred embodiments in the following with reference to the accompanying drawings.
-
FIG. 1 is a schematic diagram showing an application example of the moving target radar tracking system according to the invention (which is here encapsulated in a box indicated by the reference numeral 100). As shown, the moving target radar tracking system of theinvention 100 is designed for installation on a moving station, such as ajetfighter 10, for thejetfighter 10 to detect the position and motion of a moving target, such as an air-to-air missile (AAM) 20 that is in constant changes of position and motion relative to thejetfighter 10. During operation, when the AAM 20 is in proximity to thejetfighter 10, the moving object radar tracking system of theinvention 100 will respond to this condition by indicating the position, speed, and acceleration of theAAM 20 to the pilot of the moving target radar tracking system of theinvention 100. - As shown in
FIG. 2 , in architecture, the moving target radar tracking system of theinvention 100 comprises: (A) aradar signal emitter 110; (B) a radarsignal sensor array 120, which includes an array of N radar signal sensors that are preferably each implemented with a hybrid FSK/LFM sensors; (C) a first Gaussian-noise filter array 130, which includes N Gaussian-noise filters that are preferably each implemented with a one-stage linear Kalman filter; (D) atrilateration module 140; (E) a second Gaussian-noise filter array 150, which includes at least 3 Gaussian-noise filters data presentation module 160. The respective functions of the constituent components of the moving target radar tracking system of theinvention 100 are described in details in the following. - The
radar signal emitter 110 is used for emitting a beam of radar signal into the space under surveillance by thejetfighter 10. If an AAM 20 is in the proximity of thejetfighter 10, the radar signal beam will hit the AAM 20 and reflect as an echoed radar signal back to thejetfighter 10. - The radar
signal sensor array 120 includes an array of N radar signal sensors that are preferably implemented with a plurality of hybrid FSK/LFM sensors, each of which is based on a combination of the FSK (Frequency Shift Keying) and the LFM (Linear Frequency Modulation) techniques for extracting a set of position-motion data about theAAM 20, including the range, radial velocity, and radial acceleration of theAAM 20 based on the echoed radar signal. The number N can be 2, 3, or more. The N hybrid FSK/LFM sensors in the radarsignal sensor array 120 are respectively used for the sampling of a raw set of position-motion data, represented by {r1, v1, a1}, {r2, v2, a2}, . . . , and {rN, vN, aN}, respectively. Compared to the conventional FSK/LFM technique proposed by H. Rohling and M. M. Meinecke in the technical paper “WAVEFORM DESIGN PRINCIPLES FOR AUTOMOTIVE RADAR SYSTEMS”, it is an important aspect of the invention that the hybrid FSK/LFM sensors in the radarsignal sensor array 120 is capable of additionally acquiring the acceleration of theAAM 20, rather than just the range and velocity of the AAM 20 by this prior art. Each hybrid FSK/LFM sensor in the radarsignal sensor array 120 is designed to compute for the range r, radial velocity v, and radial acceleration a of theAAM 20 based on a modified FSK/LFM technique as described below. -
FIG. 3A a graph showing the characteristic plot of the frequency variation of an LFM signal using the conventional FSK/LFM technique (in this graph, Bsweep represents bandwidth and TLFM represents dwell time); whereasFIG. 3B is a graph showing the characteristic plot of the frequency variation of a pair of LFM signals utilized by the invention. The two LFM signals respectively have a positive slope of SA and SB. If 2N samples are to be acquired during an internal of τ=TLFM/2N, then the frequency increment over 2τ is ƒinc=Bsweep/N. In one typical application of the invention, for example, the parameters Bsweep, ƒA(t), ƒB(t), TLFM, and N are respectively Bsweep=150 MHz, ƒB(t)−ƒA(t)=300 kHz, TLFM=256 ms, and N=256. The shift in the frequency of the second LFM signal measured at the temporal point t=2n·τ from the frequency of the first LFM signal measured at the temporal point t=(2n−1)·τ is represented by ƒshift, and ƒshift=ƒB(0)−ƒA(0)+S·τ, where S=SA for the first LFM signal and S=SA for the first LFM signal. Further, the difference between the frequency of the echoed radar signal and the frequency of the originally-emitted radar signal beam is ΔƒA=ƒτA(t)−ƒA(t) for the first LFM signal, and ΔƒB=ƒτB(t)−ƒB(t) for the second LFM signal. If we define SA=ΔƒA·TLFM and SB=ΔƒB·TLFM, then during the time interval 0<t<TLFM, it can be deduced that: -
- where
- τA, vA are respectively the range and velocity of the
AAM 20 at t=(2n−1)·τ; - τB, vB are respectively the range and velocity of the
AAM 20 at t=2n·τ. - Further, the phase difference Δφ between the second LFM signal measured at t=2n·τ and the first LFM signal measured at t=(2n−1)·τ can be obtained from the following equation:
-
- Therefore, it can be deduced that:
-
- where
-
- Moreover, if we choose ƒshift=−ƒinc/2, a higher level of accuracy can be achieved for the range and velocity measurement. The output N datasets {r1, v1, a1}, {r2, v2, a2}, . . . , and {rN, vN, aN} from this radar
signal sensor array 120 are then transferred respectively to the N Gaussian-noise filters in the first Gaussian-noise filter array 130 for S/N enhancement. - The first Gaussian-
noise filter array 130 includes N Gaussian-noise filters which are preferably implemented with an array of N one-stage linear Kalman filters, each being coupled to one of the N hybrid FSK/LFM sensors in the radarsignal sensor array 120. - These N one-stage linear Kalman filters are capable of reducing the Gaussian-noise in the output datasets {r1, v1, a1}, {r2, v2, a2}, . . . , and {rN, vN, aN} from the N hybrid FSK/LFM sensors in the radar
signal sensor array 120. These N one-stage linear Kalman filters are based on a conventional Gaussian-noise filtering technology, so detailed description thereof will not be given in this specification. References about the internal structure and input-output characteristics of the one-stage linear Kalman filtering method can be found, for example, in the book “Adaptive Filter Theory”, fourth edition, authored by S. Haykin and published by Prentice Hall, 2002; and the technical paper entitled “RADAR TRACKING FOR AIR SUREILLANCE IN A STRESSFUL ENVIRONMENT USING A FUZZY-GAIN FILTER” by K. C. C. Chan et al, IEEE Trans. Fuzzy Syst. vol. 5, no. 1, pp. 80-89, June 1997. The None-stage linear Kalman filters in the first Gaussian-noise filter array 130 are used in combination to produce a collection of N S/N-enhanced sets of position-motion data about theAAM 20, which are represented by {{circumflex over (r)}1, {circumflex over (v)}1, â1}, {{circumflex over (r)}2, {circumflex over (v)}2, â2}, . . . , and {{circumflex over (r)}N, {circumflex over (v)}N, âN}, respectively. These S/N-enhanced datasets {{circumflex over (r)}1, {circumflex over (v)}1, â1}, {{circumflex over (r)}2, {circumflex over (v)}2, â2}, . . . , and {{circumflex over (r)}N, {circumflex over (v)}N, âN} are then transferred to thetrilateration module 140 for further processing. - The
trilateration module 140 is used for processing the N S/N-enhanced datasets {{circumflex over (r)}1, {circumflex over (v)}1, â1}, {{circumflex over (r)}2, {circumflex over (v)}2, â2}, . . . , {{circumflex over (r)}2, {circumflex over (v)}2, â2} from the first Gaussian-noise filter array 130 in reference to a predefined 3-dimenional (3-D) coordinate system, preferably a 3-D rectangular coordinate system having an x-axis, a y-axis, and a z-axis, to thereby obtain a collection of 3 axis-oriented sets of position-motion data respectively in reference to the x-axis, the y-axis, and the z-axis of the 3-D rectangular coordinate system. The trilateration process yields a set of position data {{circumflex over (x)}, ŷ, {circumflex over (z)}}, a set of velocity data {{circumflex over (v)}x, {circumflex over (v)}y, {circumflex over (v)}z}, and a set of acceleration data {âx, ây, âz} in accordance with the following equations (A1), (A2), and (A3): -
- The above-listed equations (A1), (A2), and (A3) are deduced as follows. Assume that the location of the (i)th hybrid FSK/LFM sensor in the radar
signal sensor array 120 is (xi, yi, zi), the originally-emitted radar signal beam hits theAAM 20 and reflects back at ({circumflex over (x)}, ŷ, {circumflex over (z)}) (which represented the detected position of the AAM 20), and theAAM 20 moves at a velocity of {{circumflex over (v)}x, {circumflex over (v)}y, {circumflex over (v)}z}). Then, in the case of N=3, the 3 hybrid FSK/LFM sensors in the radarsignal sensor array 120 can be used to respectively acquire three samples of range data {{circumflex over (r)}1, {circumflex over (r)}2, {circumflex over (r)}3}, which are mathematically expressed as follows: -
{circumflex over (r)}1 2=({circumflex over (x)}−x1)2+ŷ2+{circumflex over (z)}2 (1) -
{circumflex over (r)}2 2=({circumflex over (x)}−x2)2+ŷ2+{circumflex over (z)}2 (2) -
{circumflex over (r)}3 2={circumflex over (x)}2+(ŷ−y3)2+({circumflex over (z)}−z3)2 (3) - Note that y1=z1=y2=z2=x3=0. From (1) and (2), it can be deduced that:
-
{circumflex over (r)}1 2−({circumflex over (x)}−x1)2={circumflex over (r)}2−({circumflex over (x)}−x2)2 - Therefore, it can be deduced that:
-
- Further, it can be deduced that {{circumflex over (v)}1, {circumflex over (v)}2, {circumflex over (v)}3} is mathematically related to {{circumflex over (v)}x, {circumflex over (v)}y, {circumflex over (v)}z} as follows:
-
- From the above equations, it can be obtained that:
-
- and similarly, it can be deduced that {âx, ây, âz} is related to {â1, â2, â3} as follows:
-
- One problem in the use of this trilateration process, however, is that it would undesirably cause the 3 outputted datasets {{circumflex over (x)}, ŷ, {circumflex over (z)}}, {{circumflex over (v)}x, {circumflex over (v)}y, {circumflex over (v)}z}, and {âx, ây, âz} to be degraded in S/N. As a solution to this problem, these 3 datasets {{circumflex over (x)}, ŷ, {circumflex over (z)}}, {{circumflex over (v)}x, {circumflex over (v)}y, {circumflex over (v)}z}, {âx, ây, âz} are rearranged into three groups: {{circumflex over (x)}, {circumflex over (v)}x, âx}, {ŷ, {circumflex over (v)}y, ây}, {{circumflex over (z)}, {circumflex over (v)}z, âz}, which are then transferred to the second Gaussian-
noise filter array 150 for S/N enhancement. - The second Gaussian-
noise filter array 150 includes an array of at least 3 Gaussian-noise filters which are preferably implemented with 3 one-stage linear Kalman filters including a first Gaussian-noise filter 151, a second Gaussian-noise filter 152, and a third Gaussian-noise filter 153. The first Gaussian-noise filter 151 is used for S/N enhancement of the x-axis oriented dataset {{circumflex over (x)}, {circumflex over (v)}z, âx} to thereby obtain a noise-reduced dataset, here represented by {{tilde over (x)}, {tilde over (v)}x, ãx}; the second Gaussian-noise filter 152 is used for S/N enhancement of the y-axis oriented set of position-motion data {ŷ, {circumflex over (v)}y, ây} to thereby obtain a noise-reduced dataset, here represented by {{tilde over (y)}, {tilde over (v)}y, ãy}; and the third Gaussian-noise filter 153 is used for S/N enhancement of the z-axis oriented set of position-motion data {{circumflex over (z)}, {circumflex over (v)}z, âz} to thereby obtain a noise-reduced dataset, here represented by {{tilde over (z)}, {tilde over (v)}z, ãz}. - The
radar presentation module 160 is used to present the output S/N-enhanced datasets {{tilde over (x)}, {tilde over (v)}x, ãx}, {{tilde over (y)}, {tilde over (v)}y, ãy}, {{tilde over (z)}, {tilde over (v)}z, ãz} in human-coginzable data format for the purpose of informing the pilot of thejetfighter 10 of the position, speed, and acceleration of the threateningAAM 20. First, the output datasets {{tilde over (x)}, {tilde over (v)}x, ãx}, {{tilde over (y)}, {tilde over (v)}y, ãy}, {{tilde over (z)}, {tilde over (v)}z, ãz} from the second Gaussian-noise filter array 150 are rearranged into {{tilde over (x)}, {tilde over (y)}, {tilde over (z)}} for position, {{tilde over (v)}x, {tilde over (v)}y, {tilde over (v)}z} for velocity, and {ãx, ãy, ãz} for acceleration. These datasets are then used to drive, for example, a monitor screen (not shown) for visually presenting the position, speed, and acceleration of the threateningAAM 20 to the pilot of thejetfighter 10. - The following is a detailed description of the operation of the moving target radar tracking system of the
invention 100. In this application example, it is assumed that the moving target radar tracking system of theinvention 100 is installed on ajetfighter 10 and, during flight of thejetfighter 10, anAAM 20 is launched against thejetfighter 10. - During flight of the
jetfighter 10, the radarsignal sensor array 110 is activated to emit a beam of radar signal into the space under surveillance by thejetfighter 10. When the emitted radar signal beam hits theAAM 20, it will reflect as an echoed radar signal back to thejetfighter 10 and which is sampled by the N hybrid FSK/LFM sensors in the radarsignal sensor array 120 to produce a collection of N datasets {r1, v1, a1}, {r2, v2, a2}, . . . and {rN, vN, aN}. - Subsequently, these N datasets {r1, v1, a1}, {r2, v2, a2}, . . . , and {rN, vN, aN} are transferred to the first Gaussian-
noise filter array 130, which includes an array of N one-stage linear Kalman filters, for S/N enhancement before undergoing trilateration. The S/N-enhanced datasets {{circumflex over (r)}1, {circumflex over (v)}1, â1}, {{circumflex over (r)}2, {circumflex over (v)}2, â2}, . . . , and {{circumflex over (r)}N, {circumflex over (v)}N, âN} are then transferred to thetrilateration module 140, which is capable of processing the N S/N-enhanced datasets {{circumflex over (r)}1, {circumflex over (v)}1, â1}, {{circumflex over (r)}2, {circumflex over (v)}2, â2}, . . . , {{circumflex over (r)}2, {circumflex over (v)}2, â2} in reference to a 3-D rectangular coordinate system to thereby obtain a collection of 3 axis-oriented sets of position-motion data respectively in reference to the x-axis, the y- axis, and the z-axis of the 3-D rectangular coordinate system. The trilateration process yields a set of position data {{circumflex over (x)}, ŷ, {circumflex over (z)}}, a set of velocity data {{circumflex over (v)}x, {circumflex over (v)}y, {circumflex over (v)}z}, and a set of acceleration data {âx, ây, âz}. - Since the foregoing trilateration process might increase the level of noise in the resulted data {{circumflex over (x)}, ŷ, {circumflex over (z)}}, {{circumflex over (v)}x, {circumflex over (v)}y, {circumflex over (v)}z}, and {âx, ây, âz}, these data are rearranged into three groups: {{circumflex over (x)}, {circumflex over (v)}x, âx}, {ŷ, {circumflex over (v)}y, ây}, and {{circumflex over (z)}, {circumflex over (v)}z, âz} for further processing by the second Gaussian-
noise filter array 140 for S/N enhancement. - In the second Gaussian-
noise filter array 150, the first Gaussian-noise filter 151 is used for S/N enhancement of the x-axis oriented dataset {{circumflex over (x)}, {circumflex over (v)}x, âx}; the second Gaussian-noise filter 152 is used for S/N enhancement of the y-axis oriented dataset {ŷ, {circumflex over (v)}y, ây}; and the third Gaussian-noise filter 153 is used for S/N enhancement of the z-axis oriented dataset {{circumflex over (z)}, {circumflex over (v)}z, âz}. The resulted S/N-enhanced datasets are represented by {{tilde over (x)}, {tilde over (v)}x, ãx}, {{tilde over (y)}, {tilde over (v)}y, ãy}, and {{tilde over (z)}, {tilde over (v)}z, ãz}, respectively. - Finally, the S/N-enhanced datasets {{tilde over (x)}, {tilde over (v)}x, ãz}, {{tilde over (y)}, {tilde over (v)}y, ãy}, {otl z, {tilde over (v)}z, ãz} are transferred to the radar
data presentation module 160, which rearranges these datasets into {{tilde over (x)}, {tilde over (y)}, {tilde over (z)}} for position, {{tilde over (v)}x, {tilde over (v)}y, {tilde over (v)}z} for velocity, and {ãx, ãy, ãz} for acceleration, and then uses these position, velocity, and acceleration datasets {{tilde over (x)}, {tilde over (y)}, {tilde over (z)}}, {{tilde over (v)}x, {tilde over (v)}y, {tilde over (v)}z}, {ãx, ãy, ãz} to drive a radar monitor screen (not shown) for visually presenting the position, speed, and acceleration of the threateningAAM 20 to the pilot of thejetfighter 10. - In conclusion, the invention provides a method and system for radar tracking of a moving target (such as an air-to-air missile) from a moving station (such as a jetfighter) with improved accuracy and performance. The proposed method and system is characterized by the use of a hybrid FSK/LFM scheme for acquiring a collection of raw radar data, a first Gaussian-noise filter array of one-stage linear Kalman filters for S/N-enhancement of the raw radar data, a trilateration module, and a second Gaussian-noise filter array of one-stage linear Kalman filters for S/N-enhancement of the trilateration-resulted radar data. These features allow the radar tracking of moving objects to be more fast and accurate. The invention is therefore more advantageous to use than the prior art.
- The invention has been described using exemplary preferred embodiments. However, it is to be understood that the scope of the invention is not limited to the disclosed embodiments. On the contrary, it is intended to cover various modifications and similar arrangements. The scope of the claims, therefore, should be accorded the broadest interpretation so as to encompass all such modifications and similar arrangements.
Claims (12)
Applications Claiming Priority (2)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
TW096137781A TWI340251B (en) | 2007-10-09 | 2007-10-09 | Method and system for radar tracking of moving target from moving station |
TW096137781 | 2007-10-09 |
Publications (2)
Publication Number | Publication Date |
---|---|
US20090091490A1 true US20090091490A1 (en) | 2009-04-09 |
US7522094B1 US7522094B1 (en) | 2009-04-21 |
Family
ID=40522823
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
US11/986,531 Expired - Fee Related US7522094B1 (en) | 2007-10-09 | 2007-11-20 | Method and system for radar tracking of moving target from moving station |
Country Status (2)
Country | Link |
---|---|
US (1) | US7522094B1 (en) |
TW (1) | TWI340251B (en) |
Cited By (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2011121338A1 (en) * | 2010-04-01 | 2011-10-06 | Bae Systems Plc | Projectile detection system |
EP2407798A1 (en) * | 2010-04-01 | 2012-01-18 | BAE Systems PLC | Projectile detection system |
US20180128621A1 (en) * | 2016-11-04 | 2018-05-10 | The Boeing Company | Tracking a target moving between states in an environment |
US20180284254A1 (en) * | 2017-03-30 | 2018-10-04 | Honeywell International Inc. | Combined degraded visual environment vision system with wide field of regard hazardous fire detection system |
CN109856622A (en) * | 2019-01-03 | 2019-06-07 | 中国人民解放军空军研究院战略预警研究所 | A kind of single radar rectilinear path line target method for estimating state under constraint condition |
US10622713B2 (en) | 2015-05-26 | 2020-04-14 | Huawei Technologies Co., Ltd. | Beam signal tracking method, device and system |
US10942029B2 (en) | 2016-11-04 | 2021-03-09 | The Boeing Company | Tracking a target using multiple tracking systems |
CN116500575A (en) * | 2023-05-11 | 2023-07-28 | 兰州理工大学 | Extended target tracking method and device based on variable decibel leaf theory |
Families Citing this family (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR101514777B1 (en) | 2008-12-11 | 2015-04-24 | 삼성전자주식회사 | Terminal device and method for transmitting/receiving data thereof |
CN108872975B (en) * | 2017-05-15 | 2022-08-16 | 蔚来(安徽)控股有限公司 | Vehicle-mounted millimeter wave radar filtering estimation method and device for target tracking and storage medium |
Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US3659085A (en) * | 1970-04-30 | 1972-04-25 | Sierra Research Corp | Computer determining the location of objects in a coordinate system |
US3795911A (en) * | 1961-02-02 | 1974-03-05 | C Hammack | Method and apparatus for automatically determining position-motion state of a moving object |
US3996590A (en) * | 1961-02-02 | 1976-12-07 | Hammack Calvin M | Method and apparatus for automatically detecting and tracking moving objects and similar applications |
US5138322A (en) * | 1991-08-20 | 1992-08-11 | Matrix Engineering, Inc. | Method and apparatus for radar measurement of ball in play |
US20040119633A1 (en) * | 2000-02-08 | 2004-06-24 | Cambridge Consultants Limited | Methods and apparatus for obtaining positional information |
US20050077424A1 (en) * | 2003-05-30 | 2005-04-14 | Schneider Arthur J. | System and method for locating a target and guiding a vehicle toward the target |
US6922632B2 (en) * | 2002-08-09 | 2005-07-26 | Intersense, Inc. | Tracking, auto-calibration, and map-building system |
US20080004798A1 (en) * | 2000-12-26 | 2008-01-03 | Troxler Electronic Laboratories, Inc. | Methods, systems, and computer program products for locating and tracking objects |
Family Cites Families (1)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
JPS61205883A (en) * | 1985-03-08 | 1986-09-12 | Mitsubishi Electric Corp | Apparatus for tracking moving target |
-
2007
- 2007-10-09 TW TW096137781A patent/TWI340251B/en not_active IP Right Cessation
- 2007-11-20 US US11/986,531 patent/US7522094B1/en not_active Expired - Fee Related
Patent Citations (8)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US3795911A (en) * | 1961-02-02 | 1974-03-05 | C Hammack | Method and apparatus for automatically determining position-motion state of a moving object |
US3996590A (en) * | 1961-02-02 | 1976-12-07 | Hammack Calvin M | Method and apparatus for automatically detecting and tracking moving objects and similar applications |
US3659085A (en) * | 1970-04-30 | 1972-04-25 | Sierra Research Corp | Computer determining the location of objects in a coordinate system |
US5138322A (en) * | 1991-08-20 | 1992-08-11 | Matrix Engineering, Inc. | Method and apparatus for radar measurement of ball in play |
US20040119633A1 (en) * | 2000-02-08 | 2004-06-24 | Cambridge Consultants Limited | Methods and apparatus for obtaining positional information |
US20080004798A1 (en) * | 2000-12-26 | 2008-01-03 | Troxler Electronic Laboratories, Inc. | Methods, systems, and computer program products for locating and tracking objects |
US6922632B2 (en) * | 2002-08-09 | 2005-07-26 | Intersense, Inc. | Tracking, auto-calibration, and map-building system |
US20050077424A1 (en) * | 2003-05-30 | 2005-04-14 | Schneider Arthur J. | System and method for locating a target and guiding a vehicle toward the target |
Cited By (12)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
WO2011121338A1 (en) * | 2010-04-01 | 2011-10-06 | Bae Systems Plc | Projectile detection system |
EP2407798A1 (en) * | 2010-04-01 | 2012-01-18 | BAE Systems PLC | Projectile detection system |
US20130021195A1 (en) * | 2010-04-01 | 2013-01-24 | Bae Systems Plc | Projectile detection system |
US8981989B2 (en) * | 2010-04-01 | 2015-03-17 | Bae Systems Plc | Projectile detection system |
US10622713B2 (en) | 2015-05-26 | 2020-04-14 | Huawei Technologies Co., Ltd. | Beam signal tracking method, device and system |
US20180128621A1 (en) * | 2016-11-04 | 2018-05-10 | The Boeing Company | Tracking a target moving between states in an environment |
US10606266B2 (en) * | 2016-11-04 | 2020-03-31 | The Boeing Company | Tracking a target moving between states in an environment |
US10942029B2 (en) | 2016-11-04 | 2021-03-09 | The Boeing Company | Tracking a target using multiple tracking systems |
US20180284254A1 (en) * | 2017-03-30 | 2018-10-04 | Honeywell International Inc. | Combined degraded visual environment vision system with wide field of regard hazardous fire detection system |
US10627503B2 (en) * | 2017-03-30 | 2020-04-21 | Honeywell International Inc. | Combined degraded visual environment vision system with wide field of regard hazardous fire detection system |
CN109856622A (en) * | 2019-01-03 | 2019-06-07 | 中国人民解放军空军研究院战略预警研究所 | A kind of single radar rectilinear path line target method for estimating state under constraint condition |
CN116500575A (en) * | 2023-05-11 | 2023-07-28 | 兰州理工大学 | Extended target tracking method and device based on variable decibel leaf theory |
Also Published As
Publication number | Publication date |
---|---|
TWI340251B (en) | 2011-04-11 |
US7522094B1 (en) | 2009-04-21 |
TW200916810A (en) | 2009-04-16 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
US7522094B1 (en) | Method and system for radar tracking of moving target from moving station | |
US11988736B2 (en) | Systems and methods for virtual aperture radar tracking | |
EP0557945B1 (en) | Ranging, detection and resolving in a multislope frequency modulated waveform radar system | |
CN106537170B (en) | Distributed radar signal processing in radar system | |
US6664920B1 (en) | Near-range microwave detection for frequency-modulation continuous-wave and stepped frequency radar systems | |
CN113015922B (en) | Detection method, detection device and storage medium | |
CN100507601C (en) | Double-threshold constant false alurm motion target detecting method of double base synthetic aperture radar | |
US11346933B2 (en) | Doppler ambiguity resolution in MIMO radars using a SIMO evaluation | |
US7375675B2 (en) | Method and system for multiple target class data recording, processing and display for over-the-horizon radar | |
US20180095162A1 (en) | Apparatus and method for mitigating interference in an automotive radar system | |
US9140783B2 (en) | Radar device | |
Clemente et al. | Vibrating target micro-Doppler signature in bistatic SAR with a fixed receiver | |
CN112098990A (en) | Method for detecting and tracking medium and high speed vehicle by vehicle-mounted high-resolution millimeter wave radar | |
CN111289966A (en) | Motion information measuring method based on MIMO frequency modulation continuous wave radar coherent phase tracking | |
CN110907929A (en) | Vehicle-mounted radar target detection method and device based on double-threshold detection | |
CN111819459A (en) | Method for univocally determining object speed on radar measuring system | |
Schwarz et al. | Heartbeat measurement with millimeter wave radar in the driving environment | |
Fang et al. | Migration correction algorithm for coherent integration of low-observable target with uniform radial acceleration | |
CN110907930B (en) | Vehicle-mounted radar target detection and estimation method and device based on angle estimation | |
CN111638508B (en) | Automobile millimeter wave radar waveform design method for high-efficiency speed ambiguity resolution | |
JP4825574B2 (en) | Radar equipment | |
US20240036187A1 (en) | Velocity disambiguation for radar sensor system | |
US20230138972A1 (en) | Context based target detection | |
US20240053436A1 (en) | Method for correcting a radar signal to determine a synthetic aperture, computer program, device, and vehicle | |
US20230194657A1 (en) | Parameter Defined Stepped Frequency Waveform for Radar |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
AS | Assignment |
Owner name: NATIONAL TAIWAN UNIVERSITY, TAIWAN Free format text: ASSIGNMENT OF ASSIGNORS INTEREST;ASSIGNORS:TU, PO-JEN;KIANG, JEAN-FU;REEL/FRAME:020193/0802 Effective date: 20071018 |
|
STCF | Information on status: patent grant |
Free format text: PATENTED CASE |
|
FPAY | Fee payment |
Year of fee payment: 4 |
|
FPAY | Fee payment |
Year of fee payment: 8 |
|
FEPP | Fee payment procedure |
Free format text: MAINTENANCE FEE REMINDER MAILED (ORIGINAL EVENT CODE: REM.); ENTITY STATUS OF PATENT OWNER: SMALL ENTITY |
|
LAPS | Lapse for failure to pay maintenance fees |
Free format text: PATENT EXPIRED FOR FAILURE TO PAY MAINTENANCE FEES (ORIGINAL EVENT CODE: EXP.); ENTITY STATUS OF PATENT OWNER: SMALL ENTITY |
|
STCH | Information on status: patent discontinuation |
Free format text: PATENT EXPIRED DUE TO NONPAYMENT OF MAINTENANCE FEES UNDER 37 CFR 1.362 |
|
FP | Lapsed due to failure to pay maintenance fee |
Effective date: 20210421 |