Patent Publication Number: US-11650305-B2

Title: System for enhanced object tracking

Description:
CROSS-REFERENCE TO RELATED APPLICATIONS 
     This application is a 35 U.S.C. § 371 national phase of PCT International Application No. PCT/EP2018/065990, filed Jun. 15, 2018, which claims the benefit of priority under 35 U.S.C. § 119 to European Patent Application No. 17178908.4, filed Jun. 30, 2017, the contents of which are incorporated herein by reference in their entirety. 
     FIELD OF THE INVENTION 
     The present disclosure relates to a vehicle radar system including a control unit arrangement and at least one radar sensor arrangement that is arranged to transmit signals and receive reflected signals. The vehicle radar system is arranged to acquire a plurality of measured radar detections at different times and to engage a tracking algorithm. 
     BACKGROUND 
     Many vehicles include radar systems which are arranged for object detection, being able to provide a warning to a driver about an object in the path of a vehicle, as well as providing input to vehicle systems such as Adaptive Cruise Control (ACC) and Rear Cross Traffic Avoidance (RCTA) systems, which can provide both warnings and activate Autonomous Emergency Braking (AEB) to avoid a collision with an object behind a host vehicle. 
     Such radar systems include one or more forward-looking radar transceivers and one or more rearward-looking radar transceivers in an ego vehicle. It can be difficult to accurately estimate the heading of a remote vehicle or object, especially if the remote vehicle or object is moving in a predominantly lateral or tangential direction relative to the ego vehicle. This is for example the case when an ego vehicle is backing out from a parking space, entering a road with an oncoming remote vehicle that is driving towards a position behind the host vehicle, and in this case an RCTA system is used. 
     An RCTA system needs the velocity, distance and azimuth angle of the remote vehicle in order to determine if any warning or emergency braking is needed. In order to be able to present an early prediction, the RCTA system includes a control unit that is arranged to run a tracking algorithm that in turn is arranged to predict the movement of the remote vehicle, for example by use of a Kalman filter. 
     The radar sensors will obtain a plurality of detections from the remote vehicle, and each radar scan will return different points. This in turn leads to tangential velocity uncertainty as well as angular noise, which is detrimental for a tracking algorithm that needs a certain amount of consistent radar detections in order to be able predict the movement of the remote vehicle to a sufficient degree. 
     The quicker the tracking algorithm can produce a sufficient prediction of the movement of the remote vehicle, the earlier the RCTA system can determine whether any action is needed. 
     RCTA systems are described in US 2016/291149 and US 2008/306666, where camera data is used together with radar data. 
     Generally, it is desirable that a tracking algorithm produces a sufficient prediction of the movement of a remote vehicle or other target object as quick as possible, regardless of if the tracking algorithm is used in an RCTA system or for any other relevant purposes such as for example general collision avoidance or automatic and/or assisted driving. 
     The object of the present disclosure is to provide a radar system that includes a tracking algorithm that is arranged to predict the movement of a remote vehicle or other target object to a sufficient degree in a quicker and more reliable manner than before without having to add further components. 
     SUMMARY AND INTRODUCTORY DESCRIPTION OF PREFERRED EMBODIMENTS 
     The above-described object is obtained by embodiments of a vehicle radar system including a control unit arrangement and at least one radar sensor arrangement that is arranged to transmit signals and receive reflected signals. The vehicle radar system is arranged to acquire a plurality of measured radar detections at different times. The control unit arrangement is arranged to engage a tracking algorithm using the present measured radar detections as input such that at least one track is initialized. For each track, the control unit arrangement is arranged to calculate a calculated previous radar detection that precedes the present measured radar detections, and to re-initialize the tracking algorithm using the present measured radar detections in combination with the calculated previous radar detection. 
     The above-described object is also obtained by embodiments of the present invention including a method for a vehicle radar system, where the method includes transmitting signals and receiving reflected signals, and acquiring a plurality of measured radar detections at different times. The method further includes engaging a tracking algorithm using the present measured radar detections as input such that at least one track is initialized. For each track, the method includes calculating a calculated previous radar detection that precedes the present measured radar detections, and re-initializing the tracking algorithm using the present measured radar detections in combination with the calculated previous radar detection. 
     According to some aspects of embodiments of the present invention, for each track, for each one of a plurality of measured radar detections, the control unit arrangement is arranged to calculate a corresponding predicted detection and a corresponding corrected predicted detection. The control unit arrangement is furthermore arranged to calculate a corresponding distance vector, an innovation vector, that runs between a present measured radar detection and a corresponding present predicted detection. Each innovation vector is constituted by a vector component of a first vector type and of a vector component of a second vector type. The control unit arrangement is arranged to calculate a statistical distribution of a plurality of at least one of the vector types, and to determine how the calculated statistical distribution is related to another statistical distribution, and/or to determine symmetrical characteristics of the calculated statistical distribution. The control unit arrangement is then arranged to either maintain or re-initialize the tracking algorithm in dependence of the determined result that provides data for quality measures of the track. 
     According to some aspects of embodiments of the present invention, the another statistical distribution is constituted by a predetermined statistical distribution where the control unit arrangement is arranged to determine to which extent the calculated statistical distribution deviates from the predetermined statistical distribution. If the deviation is determined to exceed a predefined threshold, the control unit arrangement is arranged to re-initialize the tracking algorithm. 
     According to some aspects of embodiments of the present invention, the another statistical distribution is constituted by a statistical distribution of components of the corresponding measured radar detections, where the control unit arrangement is arranged to determine a ratio between the calculated statistical distribution and the another statistical distribution. If the ratio is determined to deviate beyond a predefined threshold, the control unit arrangement is arranged to re-initialize the tracking algorithm. 
     Other examples of embodiments of the present invention are disclosed in this disclosure. 
     A number of advantages are obtained by use of embodiments of the present invention. Mainly, a tracking algorithm is provided that produces a sufficient prediction of the movement of a remote vehicle as quick as possible. 
    
    
     
       BRIEF DESCRIPTION OF THE DRAWINGS 
       The present disclosure will now be described more in detail with reference to the appended drawings, where: 
         FIG.  1    shows a schematic top view of an ego vehicle; 
         FIG.  2    shows a schematic top view of the ego vehicle and an approaching target vehicle; 
         FIG.  3    shows measured detections, predicted detections and corrected detections at different times; 
         FIG.  4    shows measured detections, predicted detections and corrected detections at different times, as well as an innovation vector according to a first example; 
         FIG.  5    shows a statistical distribution for innovation vector components; 
         FIG.  6    shows a statistical distribution for innovation vector components parts and a predetermined statistical distribution; 
         FIG.  7    shows a measured detection and a predicted detection as well as an innovation vector according to a second example; 
         FIG.  8    shows a first statistical distribution for innovation vector components and a first statistical distribution for measured detection components; 
         FIG.  9    shows a second statistical distribution for innovation vector components and a second statistical distribution for measured detection components; and 
         FIG.  10    shows a flowchart for a method according to the present disclosure. 
     
    
    
     DETAILED DESCRIPTION 
       FIG.  1    schematically shows a top view of an ego vehicle  1  arranged to run on a road  2  in a forward direction F, where the ego vehicle  1  includes a vehicle radar system  3 . The vehicle radar system  3  includes a rear radar sensor arrangement  4  that is arranged to distinguish and/or resolve single targets  5  from the surroundings by transmitting signals  6  and receiving reflected signals  7  and using a Doppler effect in a previously well-known manner. The transmitted signals  6  are according to some aspects constituted by sweep signals in the form of FMCW (Frequency Modulated Continuous Wave) chirp signals  6  of a previously known kind. 
     The vehicle radar system  3  further includes a control unit arrangement  8  that is connected to the rear radar sensor arrangement  4  and is arranged to provide azimuth angles of possible target objects  5  by simultaneously sampling and analyzing phase and amplitude of the received signals in a previously well-known manner. In  FIG.  1   , one radar detection  9  is shown, having a certain detected azimuth angle (p relative a radar reference line  22 ; suitably a radar sensor arrangement boresight direction, distance r and radial velocity v. 
     As shown in  FIG.  2   , an approaching target vehicle  31  is moving towards the ego vehicle with a velocity v target , and is detected by use of the rear radar sensor arrangement  4 . There is a plurality of measured radar detections measured by the rear radar sensor arrangement  4  at different times; at an initial time t 0  there is one radar detection  10  that is preceded by three previous radar detection  11 ,  12 ,  13  at three corresponding previous times t −1 , t −2 , t −3 . With reference also to  FIG.  3   , each measured radar detection  10 ,  11 ,  12 ,  13  has a certain corresponding measured azimuth angle φ 0 , φ −2 , φ −3 , distance r 0 , r −1 , r −2 , r −3 , and radial velocity v 0 , v −1 , v −2 , v −3 . All azimuth angles φ 0 , φ −1 , φ −2 , φ −3  are defined relative the radar reference line  22 . 
     The control unit arrangement  8  is arranged to engage a tracking algorithm using a Kalman filter at the initial time t 0  using the present four measured radar detections  10 ,  11 ,  12 ,  13  as input. The central component of a tracking algorithm is the filtering of the tracks. The used filter algorithm can be chosen freely. A Kalman filter is common, but there is a huge variety of filters, e.g. α-β-filters or α-β-γ-filters. A track is in this context defined by at least a filter state that consists of the position and its derivatives; at least velocity, but can contain also acceleration and higher derivatives. It is desired to have a reliable track engaged as early as possible, when a distance d between the vehicles  1 ,  31  is as large as possible. 
     According to the present disclosure, the control unit arrangement  8  is arranged to use the tracking algorithm to calculate a calculated previous radar detection  14  that precedes the present four measured radar detections  10 ,  11 ,  12 ,  13  at a corresponding previous time t −4 , where the calculated previous radar detection  14  has a certain corresponding calculated azimuth angle φ −4 , distance r −4 , and radial velocity v −4 . 
     The control unit arrangement  8  is arranged to re-start the tracking algorithm using the present four radar detections  10 ,  11 ,  12 ,  13  and the calculated previous radar detection  14 , and then calculate a next calculated radar detection  15  at a corresponding next time t +1 . At the next time t +1 , the rear radar sensor arrangement  4  has also detected a next measured radar detection  16  that corresponds to the next calculated radar detection  15 . At a yet next time t +2 , the rear radar sensor arrangement  4  has detected a following measured radar detection  17 . In  FIG.  3   , no azimuth angle, distance, and radial velocity is indicated for the last detection  15 ,  16 ,  17  for reasons of clarity. 
     The calculated radar detection above are predicted radar detections before correction in the tracking algorithm. In the following, general measured radar detections, predicted radar detections and corrected radar detection for a running tracking algorithm will be discussed. 
     With reference to  FIG.  4   , a further aspect of the present disclosure will be discussed. Here, in a first example of the further aspect, a first predicted radar detection x t | t−1 | and a first measured radar detection z t  at a time t are shown. The first predicted radar detection x t | t−1 | is corrected such that a first corrected radar detection x t | t | is formed at the time t. At a next time t+1, corresponding to a following radar cycle, the procedure continues in a well-known manner such that a second measured radar detection z t+1 , a second predicted radar detection x t+1 |t| and a second corrected radar detection x t+1 | t+1 | is obtained at the time t+1. Here x i | j | denotes a predicted radar detection at a time i when j=i−1, and a corrected radar detection at a time i when j=i. 
     The first measured radar detection z t  has a measured velocity vector m 1 , the first predicted radar detection x t | t−1 | has a predicted velocity vector p 1  and the first corrected radar detection x t |t| has a first corrected velocity vector c 1 . Between the first predicted radar detection x t | t−1 | and the first measured radar detection z t  there is a distance that corresponds to a so-called filter residium or a first innovation vector  18  that runs from the first predicted radar detection x t | t−1 | to the first measured radar detection z t . The first innovation vector  18  is constituted by two components, a first main component  18   a  that runs along the predicted velocity vector p 1  and a first perpendicular component  18   b  that is perpendicular to the first main component  18   a.    
     Correspondingly, at the next time t+1, the second measured radar detection z t+1  has a measured velocity vector m 2 , the second predicted radar detection x t+1 | t | has a predicted velocity vector p 2  and the second corrected radar detection x t+1 | t+1 | has a second corrected velocity vector c 2 . Between the second predicted radar detection x t+1 | t | and the second measured radar detection z t+1  there is a second innovation vector  23 . The second innovation vector  23  is constituted by two components, a second main component  23   a  that runs along the predicted velocity vector p 2  and a second perpendicular component  23   b  that is perpendicular to the second main component  23   a.    
     In accordance with the present disclosure, with reference also to  FIG.  5    and  FIG.  6   , the control unit arrangement  8  is arranged to determine a plurality of perpendicular components  18   b ,  23   b  for a corresponding plurality of radar cycles, and to calculate a statistical distribution  24  for the perpendicular components  18   b ,  23   b . The control unit arrangement  8  is then arranged to determine to which extent the calculated statistical distribution deviates from a predetermined statistical distribution  25 , according to some aspects a normal, or Gaussian, distribution, and/or its symmetrical characteristics such as symmetry around a zero point. If the deviation exceeds a predefined threshold, the tracking algorithm is re-started. According to some aspects, the plurality of perpendicular components  18   b ,  23   b  is constituted by about 10 to 30 perpendicular components. 
     The main components  18   a ,  23   a  are dependent on the predicted velocity vector p 1 , p 2 . According to some aspects, as an alternative or as an addition, the control unit arrangement  8  is arranged to determine a plurality of main components for a corresponding plurality of radar cycles, and to calculate a statistical distribution for said main components. The control unit arrangement  8  is then arranged to determine to which extent the calculated statistical distribution is related to the direction of the track. If the calculated statistical distribution is pointing to the rear of the track, the track is too fast, and if the calculated statistical distribution is pointing to the front of the track, the track is too slow. 
     In other words, it is also here determined whether the calculated statistical distribution  24  deviates from a predetermined statistical distribution  25 , according to some aspects a normal, or Gaussian, distribution, and/or its symmetrical characteristics such as symmetry around a zero point. If the deviation exceeds a predefined threshold, the tracking algorithm is re-started in this case as well. 
     In the following, with reference to  FIG.  7   , a second example of the further aspect will be provided where polar coordinates are used. The first predicted radar detection x t | t−1 | has a certain calculated azimuth angle φ p , distance r p , and radial velocity v p , while the first measured radar detection z t  has a certain measured azimuth angle φ m , distance r m , and radial velocity v m . The azimuth angles φ p , φ m  are measured from the radar reference line  22 . Between the azimuth angles φ p , φ m  there is a difference angle Δφ, and between the distances r p , r m  there is a difference distance Δr. 
     As in the previous example, between the first predicted radar detection x t | t−1 | and the first measured radar detection z t  there is a distance that corresponds to an innovation vector  19 . The innovation vector  19  is constituted by two components, an angular component, the difference angle Δφ, and a radial component, the difference distance Δr. For reasons of clarity only one measured radar detection z t  and predicted radar detection x t | t−1 | are shown n  FIG.  6   . Of course the predicted radar detection x t | t−1 | has a corresponding corrected radar detection, and of course a plurality of measured radar detections, predicted radar detections and predicted radar detections is obtained during a plurality of radar cycles. 
     In accordance with the present disclosure, with reference also to  FIG.  8   , the control unit arrangement  8  is arranged to determine a plurality of angular components Δφ, and a plurality of measured azimuth angles φ m , for a corresponding plurality of radar cycles, and to calculate a first angular statistical distribution σ inno,φ  for the angular parts components Δφ and a second angular statistical distribution σ meas,φ  for the measured azimuth angles φ m . The control unit arrangement  8  is then arranged to determine an angular noise ratio by dividing the first angular statistical distribution σ inno,φ  with the second angular statistical distribution σ meas,φ . 
     Correspondingly, with reference also to  FIG.  9   , the control unit arrangement  8  is arranged to determine a plurality of radial components Δr, and a plurality of measured distances r m , for a corresponding plurality of radar cycles, and to calculate a first distance statistical distribution σ inno,r  for the radial components Δr and a second distance statistical distribution σ meas,r  for the measured distances r m . The control unit arrangement  8  is then arranged to determine a range noise ration by dividing the first distance statistical distribution σ inno,r  with the second distance statistical distribution σ meas,r . 
     In this way it can be determined if the statistical distributions σ inno,φ , σ inno,r  of the innovation vector components Δφ, Δr are wider than the measurement noise, and to which degree. If there is a deviation, that is determined to deviate beyond a predefined threshold, the tracking algorithm is re-started as in the first example. 
     According to some aspects, the statistical distributions σ inno,φ , σ inno,r , σ meas,φ , σ meas,r  are constituted by normal, or Gaussian, distributions. 
     According to some aspects, between two adjacent times, a radar cycle has passed. In this context, a radar cycle is one observation phase during which the vehicle radar system  2  is arranged to acquire data, process the data on several signal processing levels and to send out available results. This can be a fixed time interval, or it can be a dynamic time interval depending on environment conditions and processing load. 
     By use of the present disclosure, that can be used for any type of vehicle radar sensor arrangement, it can be determined whether a certain track fulfills certain quality measures or not, and if not, the tracking algorithm can be re-started or re-initialized. The quality measures define how well a certain track fits corresponding measurement. A core of the present disclosure lies not that the statistical distribution of innovation vector components  18   a ,  18   b ; Δφ, Δr are determined and investigated. The investigation result provides data for said quality measures. 
     According to some aspects, a tracking procedure follows the following steps:
         Step  1 : Consistent measurements are searched over several measurement cycles. If a consistency is found, a track is opened. Opening a track use finding good initial values of the filter state space. This is often a crucial component, as not many measurements are available. A list of track is obtained over time.   Step  2 : The state space is predicted to the next measurement cycle   Step  3 : In the next radar cycle, measurements are searched that probably belong to tracks. These measurements are associated to the tracks. If no association is found, no correction is made. Each state space is corrected by its associated measurement.   Step  4 : If a track is not going to be discontinued, continue with point  2 , else remove the track from the list.       

     As indicated in  FIG.  1   , the ego vehicle  1  includes a safety control unit  20  and safety system  21 , for example an emergency braking system and/or an alarm signal device. The safety control unit  20  is arranged to control the safety system  21  in dependence of input from the radar system  3 . Such input may be input via the control unit arrangement  8 . 
     With reference to  FIG.  10   , the present disclosure also relates to a method for a vehicle radar system  3 , where the method includes the steps of:
         Step  26 : Transmitting signals  6  and receiving reflected signals  7 .   Step  27 : Acquiring a plurality of measured radar detections  10 ,  11 ,  12 ,  13  at different times.   Step  28 : Engaging a tracking algorithm using the present measured radar detections  10 ,  11 ,  12 ,  13  as input such that at least one track is initialized. For each track, the method includes:   Step  29 : Calculating a calculated previous radar detection  14  that precedes the present measured radar detections  10 ,  11 ,  12 ,  13 .   Step  30 : Re-initializing the tracking algorithm using the present measured radar detections  10 ,  11 ,  12 ,  13  in combination with the calculated previous radar detection  14 .       

     The present disclosure is not limited to the examples above, but may vary freely within the scope of the appended claims. For example, the radar system may be implemented in any type of vehicle such as cars, trucks and buses as well as boats and aircraft. 
     The statistical distributions  24 ,  25 ; σ inno,φ , σ meas,φ ; σ inno,r , σ meas,r , shown are only examples of statistical distributions that are used for explaining the present disclosure. The statistical distributions  24 ,  25 ; σ inno,φ , σ meas,φ ; σ inno,r , σ meas,r , can have any forms possible and/or suitable within the scope of the present disclosure. 
     Exactly how data processing, such as calculations and determining procedures, is accomplished in practice may vary, the example disclosed above is only an example. The control unit arrangement  8  may be comprised by one or more separate or integrated control units. The safety control unit  20  is according to some aspects included in the control unit arrangement  8 . 
     In the examples discussed there is a tracked target vehicle; generally there can be any type of tracked target object such as for example a bicycle or a pedestrian. 
     Other kinds of FMCW signals and FMCW signal configurations are also conceivable, as well as other types of Doppler radar signals. Other types of radar systems are also conceivable; not only FMCW radar systems are conceivable. Pulse radar, FSK (frequency-shift keying) or CW (continuous wave) waveform are also conceivable like all other kinds of suitable modulation techniques. 
     The schematics of vehicle radar systems are simplified, only showing components that are considered relevant for an adequate description of the present disclosure. It is understood that the general design of radar systems of this kind is well-known in the art. 
     A rear vehicle radar system is shown in  FIG.  1    and  FIG.  2   , but the examples above are of course applicable for any type of vehicle radar system at any position in a vehicle. 
     Wordings such as perpendicular are not intended to be understood as mathematically exact, but within what is practically obtainable in the present context. 
     Generally, the present disclosure relates to a vehicle radar system  3  including a control unit arrangement  8  and at least one radar sensor arrangement  4  that is arranged to transmit signals  6  and receive reflected signals  7 , where the vehicle radar system  3  is arranged to acquire a plurality of measured radar detections  10 ,  11 ,  12 ,  13  at different times; where the control unit arrangement  8  is arranged to engage a tracking algorithm using the present measured radar detections  10 ,  11 ,  12 ,  13  as input such that at least one track is initialized. For each track, the control unit arrangement  8  is arranged to:
         calculate a calculated previous radar detection  14  that precedes the present measured radar detections  10 ,  11 ,  12 ,  13 ; and to   re-initialize the tracking algorithm using the present measured radar detections  10 ,  11 ,  12 ,  13  in combination with the calculated previous radar detection  14 .       

     According to some aspects, the plurality of measured radar detections  10 ,  11 ,  12 ,  13  constitutes at least four measured radar detections  10 ,  11 ,  12 ,  13 . 
     According to some aspects, the tracking algorithm includes a Kalman filter. 
     According to some aspects, for each track, for each one of a plurality of measured radar detections z t , z t+1 , the control unit arrangement  8  is arranged to calculate a corresponding predicted detection x t|t−1| , x t+1|t|  and a corresponding corrected predicted detection x t|t| , x t+1|t+1| , and to furthermore calculate a corresponding distance vector, an innovation vector  18 ,  19 , that runs between a present measured radar detection z t  and a corresponding present predicted detection x t|t−1| , where each innovation vector  18 ,  19  is constituted by a vector component of a first vector type  18   a , Δφ and of a vector component of a second vector type  18   b , Δr, where the control unit arrangement  8  is arranged to:
         calculate a statistical distribution  24 ; σ inno,φ , σ inno,r  of a plurality of at least one of the vector types  18   a , Δφ;  18   b , Δr;   determine how the calculated statistical distribution  24 ; σ inno,φ , σ inno,r  is related to another statistical distribution  25 ; σ meas,φ , σ meas,r ; and/or   determine symmetrical characteristics of the calculated statistical distribution  24 ; σ inno,φ , σ inno,r ;   and to either maintain or re-initialize the tracking algorithm in dependence of the determined result that provides data for quality measures of the track.       

     According to some aspects, the another statistical distribution is constituted by a predetermined statistical distribution  25 , where the control unit arrangement  8  is arranged to determine to which extent the calculated statistical distribution deviates from the predetermined statistical distribution  25 , and if the deviation is determined to exceed a predefined threshold, to re-initialize the tracking algorithm. 
     According to some aspects, the another statistical distribution is constituted by a statistical distribution σ meas,φ , σ meas,r  of components of the corresponding measured radar detections z t , z t+1 , where the control unit arrangement  8  is arranged to determine a ratio between the calculated statistical distribution σ inno,φ , σ inno,r  and the another statistical distribution σ meas,φ , σ meas,r , and if the ratio is determined to deviate beyond a predefined threshold, to re-initialize the tracking algorithm. 
     Generally, the present disclosure also relates to a method for a vehicle radar system  3 , where the method includes the steps of:
         Step  26 : transmitting signals  6  and receiving reflected signals  7 ;   Step  27 : acquiring a plurality of measured radar detections  10 ,  11 ,  12 ,  13  at different times;   Step  28 : engaging a tracking algorithm using the present measured radar detections  10 ,  11 ,  12 ,  13  as input such that at least one track is initialized. For each track, the method includes:   Step  29 : calculating a calculated previous radar detection  14  that precedes the present measured radar detections  10 ,  11 ,  12 ,  13 ; and   Step  30 : re-initializing the tracking algorithm using the present measured radar detections  10 ,  11 ,  12 ,  13  in combination with the calculated previous radar detection  14 .       

     According to some aspects, the plurality of measured radar detections  10 ,  11 ,  12 ,  13  constitutes at least four measured radar detections  10 ,  11 ,  12 ,  13 . 
     According to some aspects, the tracking algorithm uses a Kalman filter. 
     According to some aspects, for each track, for each one of a plurality of measured radar detections z t , z t+1 , the method includes calculating a corresponding predicted detection x t|t−1| , x t+1|t|  and a corresponding corrected predicted detection x t|t| , x t+1|t+1| , and calculating a corresponding distance vector, an innovation vector  18 ,  19 , that runs between a present measured radar detection z t  and a corresponding present predicted detection x t|t−1| , where each innovation vector  18 ,  19  is constituted by a vector component of a first vector type  18   a , Δφ and of a vector component of a second vector type  18   b , Δr, where the method further includes the steps of:
         calculating a statistical distribution  24 ; σ inno,φ , σ inno,r  of a plurality of at least one of the vector types  18   a , Δφ;  18   b , Δr;   determining how the calculated statistical distribution  24 ; σ inno,φ , σ inno,r  is related to another statistical distribution  25 ; σ meas,φ , σ meas,r ; and/or   determining symmetrical characteristics of the calculated statistical distribution  24 ; σ inno,φ , σ inno,r ; and either   maintaining or re-initializing the tracking algorithm in dependence of the determined result that provides data for quality measures of the track.       

     According to some aspects, the another statistical distribution is constituted by a predetermined statistical distribution  25 , where the control unit arrangement  8  is arranged to determine to which extent the calculated statistical distribution deviates from the predetermined statistical distribution  25 , and if the deviation is determined to exceed a predefined threshold, to re-initialize the tracking algorithm. 
     According to some aspects, the another statistical distribution is constituted by a statistical distribution σ meas,φ , σ meas,r  of components of the corresponding measured radar detections z t , z t+1 , where the control unit arrangement  8  is arranged to determine a ratio between the calculated statistical distribution σ inno,φ , σ inno,r  and the another statistical distribution σ meas,φ , σ meas,r , and if the ratio is determined to deviate beyond a predefined threshold, to re-initialize the tracking algorithm. 
     While the above description constitutes the preferred embodiment of the present invention, it will be appreciated that the invention is susceptible to modification, variation and change without departing from the proper scope and fair meaning of the accompanying claims.