CN113790735B - Pedestrian single-step dividing method under complex motion state - Google Patents
Pedestrian single-step dividing method under complex motion state Download PDFInfo
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Abstract
The invention provides a single-step pedestrian dividing method under a complex motion state, which comprises the steps of firstly, collecting acceleration and angular velocity data under various traveling states and non-traveling states, calculating vertical acceleration to perform zero-crossing detection, and extracting a peak value and a trough value of the acceleration based on a zero-crossing point; then, introducing time-frequency constraint based on an empirical value of a gait cycle, introducing amplitude constraint based on a minimum threshold of an acceleration peak value, and judging whether the peak-valley value meets two constraint conditions; in addition, calculating a pitch angle through angular velocity data, establishing pitch angle constraint, judging whether a pedestrian is in a squatting state, collecting forward and vertical acceleration information, establishing two-dimensional acceleration constraint, and judging whether the pedestrian is in a jump-in-place state; through the judgment, whether the two adjacent zero crossing intervals including the wave crest and the wave trough contain an effective single step or not is determined and divided. The method can effectively improve single-step division precision and realize high-precision dead reckoning of pedestrians in a complex motion state.
Description
Technical Field
The invention belongs to the technical field of pedestrian navigation based on micro inertial sensors, and particularly relates to a pedestrian single-step dividing method under a complex motion state.
Background
The single-step division is the basis of dead reckoning of pedestrians based on inertial information, and specific methods include a peak detection method, a threshold method, a sliding average method and the like. When the traditional pedestrian dead reckoning technology utilizes a peak detection method to carry out single-step division, a peak point of acceleration or angular velocity needs to be found, and two adjacent peaks are regarded as one step, but the pedestrian also has a peak in a non-advancing motion state, and meanwhile, pseudo-peak interference exists in an advancing state, so that the division precision is not beneficial to improvement.
Disclosure of Invention
The invention aims to provide a single-step pedestrian dividing method under a complex motion state, which can effectively improve the single-step dividing precision and dead reckoning precision of pedestrians and solve the problem of interference of non-travelling motion on single-step dividing in the process of proceeding.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
the invention provides a single-step pedestrian dividing method under a complex motion state, which comprises the following steps of
Collecting acceleration and angular velocity data in various traveling states and non-traveling states;
calculating vertical acceleration to perform zero crossing detection, and extracting a wave peak value and a wave trough value of the acceleration based on a zero crossing point;
establishing time-frequency constraint based on an empirical value of a gait cycle, establishing amplitude constraint based on a minimum threshold of an acceleration peak value, and judging whether the time difference between acceleration peak and valley and the acceleration amplitude meet two constraint conditions or not;
establishing pitch angle constraint based on an empirical value of pitch angle change in the squatting process, calculating the pitch angle according to the angular speed data, and judging whether the pitch angle meets constraint conditions or not;
establishing two-dimensional acceleration constraint based on an empirical value of acceleration change in the jumping process, calculating forward and vertical accelerations, and judging whether the accelerations in the two directions meet constraint conditions or not;
judging whether two adjacent zero crossing intervals containing wave crests and wave troughs contain an effective single step or not according to the constraint conditions, and dividing.
Further, the pedestrian single-step dividing method further comprises the step of updating the single-step detection interval by adopting a dynamic sliding window method.
Further, the method for judging whether the two adjacent zero crossing intervals including the wave crest and the wave trough include an effective single step or not is as follows: if the acquired data in two adjacent intervals meet the time-frequency constraint and the amplitude constraint but do not meet the pitch angle constraint and the two-dimensional acceleration constraint, the two adjacent intervals contain an effective single step; if the acquired data in the two adjacent intervals does not meet at least one of time-frequency constraint and amplitude constraint or meet at least one of pitch angle constraint and two-dimensional acceleration constraint, the two adjacent intervals do not contain an effective single step.
Further, the travel motion includes walking, running, and the non-travel motion includes shaking, in-situ turning, squatting, in-situ jumping.
Further, the zero-crossing detection method specifically comprises the following steps of
Calculating the vertical acceleration at the moment t as
wherein ,the vertical acceleration acquired at the moment t is the local standard gravity acceleration g;
when the following condition is satisfied:
A t-T A T ≤0
record A t Is thatI.e. zero crossing, corresponding moment +.>For the zero crossing time, the zero crossing points are calculated in turn> Corresponding zero crossing time->T is the sampling period.
Further, the method for extracting the peak value and the trough value of the acceleration comprises the following steps of
Find outPeak value +.>And (2) the valley value>Corresponding zero crossing time->
wherein ,|At | max Represents the maximum value of the absolute value of the acceleration in the zero crossing point interval S 1 、S 2 Respectively positive and negative signs.
Further, the time-frequency constraint is that
wherein ,ThUpper part 、Th Lower part(s) Is the upper and lower limit empirical value of gait cycle;
the amplitude constraint is that
wherein ,Aexp Represents the minimum threshold of acceleration peak value, A D Representing the maximum threshold of the peak-to-valley difference.
Further, the pitch angle is constrained to be
Wherein, pitch init Standing for human bodyInitial pitch at time, pitch t Pitch angle (pitch) calculated for time t using the acquired angular velocity t ) min For pitch angle pitch t At the position ofMinimum value of interval D exp Is an empirical threshold.
Further, the two-dimensional acceleration constraint is that
wherein ,axt Is the forward acceleration of the pedestrian at time t, and />Respectively-> and />In the intervalMaximum value of M exp1 and Mexp2 Is an empirical threshold.
Further, ifThe interval comprises effective single steps, the adjacent wave peak points are divided into one single step, and the next detection interval is updated to +.>If->The interval does not contain an effective single step, and the next detection interval is updated to +.>
Compared with the prior art, the invention has the beneficial effects that:
the invention provides a single-step division method for pedestrians in a complex motion state, which greatly improves single-step division precision by introducing time-frequency constraint, amplitude constraint, pitch angle constraint and two-dimensional acceleration constraint and realizes high-precision dead reckoning of pedestrians in the complex motion state.
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The accompanying drawings, which are included to provide a further understanding of embodiments of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention. It is evident that the drawings in the following description are only some embodiments of the present invention and that other drawings may be obtained from these drawings without inventive effort for a person of ordinary skill in the art.
Fig. 1 is a schematic diagram of a single-step pedestrian dividing method in a complex motion state according to an embodiment of the present invention.
Detailed Description
Specific embodiments of the present invention are described in detail below. In the following description, for purposes of explanation and not limitation, specific details are set forth in order to provide a thorough understanding of the present invention. It will be apparent, however, to one skilled in the art that the present invention may be practiced in other embodiments that depart from these specific details.
It should be noted that, in order to avoid obscuring the present invention due to unnecessary details, only the device structures and/or processing steps closely related to the aspects of the present invention are shown in the drawings, while other details not greatly related to the present invention are omitted.
The single step division is the basis for dead reckoning by pedestrians based on inertial information. In a complex motion state, in order to eliminate the interference of various non-advancing motion modes, the invention introduces two conditions of time-frequency constraint and amplitude constraint to judge whether an acceleration peak-valley interval is an effective single step, and provides pitch angle constraint and two-dimensional acceleration constraint to distinguish non-advancing motions such as couplet squatting, in-situ jump and the like, so that the single step dividing precision can be greatly improved. The method is particularly suitable for solving the application requirements of high-precision positioning navigation of pedestrians in complex motion states.
The basic principle of the invention is as follows: binding a micro inertial sensor on the waist, and collecting acceleration and angular velocity data in various traveling states and non-traveling states; zero-crossing detection is carried out by utilizing the vertical acceleration signal, and the values of the wave crest and the wave trough are extracted based on the zero-crossing point; based on the empirical value of gait cycle, introducing time-frequency constraint, and based on the minimum threshold of acceleration peak value, introducing amplitude constraint, judging whether the peak-valley value meets two constraint conditions; calculating a pitch angle based on the collected angular velocity data, and introducing pitch angle constraint to judge whether the pedestrian is in a squatting state; based on the collected forward and vertical acceleration information, introducing two-dimensional acceleration constraint, and judging whether the pedestrian is in a jump-in-place state; and judging whether the interval comprises an effective single step or not based on 4 judging conditions, dividing the interval, and updating the single step detection interval by adopting a dynamic sliding window method.
The invention provides a single-step pedestrian dividing method under a complex motion state, which specifically comprises the following steps:
collecting acceleration and angular velocity data in various traveling states and non-traveling states;
calculating a vertical acceleration signal to perform zero crossing detection, and extracting a peak value and a trough value of the acceleration signal based on a zero crossing point;
establishing time-frequency constraint based on an empirical value of a gait cycle, establishing amplitude constraint based on a minimum threshold of an acceleration peak value, and judging whether the time difference and the amplitude between acceleration peak and valley meet two constraint conditions or not;
establishing pitch angle constraint based on an empirical value of pitch angle change in the squatting process, calculating the pitch angle according to the angular speed data, and judging whether the pitch angle meets constraint conditions or not;
establishing two-dimensional acceleration constraint based on an empirical value of acceleration change in the jumping process, calculating forward and vertical acceleration information, and judging whether the acceleration in two directions meets constraint conditions or not;
judging whether two adjacent zero crossing intervals containing wave crests and wave troughs contain an effective single step or not according to the constraint conditions, and dividing.
The method for judging whether the single step is included is as follows: if the inertial data in the two adjacent intervals meet the time-frequency constraint and the amplitude constraint but do not meet the pitch angle constraint and the two-dimensional acceleration constraint, the two adjacent intervals contain an effective single step, and if the inertial data in the two adjacent intervals do not meet at least one of the time-frequency constraint and the amplitude constraint or meet at least one of the pitch angle constraint and the two-dimensional acceleration constraint, the two adjacent intervals do not contain an effective single step.
Meanwhile, the pedestrian single-step dividing method under the complex motion state can also update the single-step detection interval by adopting a dynamic sliding window method.
The technical scheme of the invention is described in detail below in connection with a specific embodiment. As shown in fig. 1, the specific method is as follows:
(1) Inertial data acquisition
Binding the micro inertial sensor on the waist of a pedestrian, and collecting original inertial data under various traveling motion states and non-traveling motion states, wherein the traveling motion comprises actions such as walking and running, and the non-traveling motion comprises actions such as shaking, in-situ turning, squatting and in-situ jumping.
(2) Zero crossing detection
The vertical acceleration obtained by subtracting the gravity acceleration from the moment t is calculated as follows:
wherein ,and g is the local standard gravitational acceleration. Sampling period is denoted by TA period when the following condition is satisfied:
A t-T A T ≤0
record A t Is thatI.e. zero crossing, corresponding moment +.>Is the zero crossing time. Sequentially buffer->And recording the corresponding moment +.>
(3) Extracting peak-valley value
Find outPeak value +.>And (2) the valley value>And recording the corresponding moment +.>Sign S 1 and S2 The method comprises the following steps:
wherein ,|At | max The maximum value of the absolute value of the acceleration in this section is shown.
(4) Multi-condition amplitude-frequency detection
In order to eliminate the interference of non-travelling motion modes such as in-situ shaking, turning circle and the like, and avoid false detection of virtual detection and local false value caused by body shaking, two conditions of time-frequency constraint and amplitude constraint are introduced to judge an effective single step based on the found acceleration peak-valley value. Since the time difference between the acceleration peaks and valleys is half of a single step period, the time-frequency constraint is:
wherein ,ThUpper part 、Th Lower part(s) Is the upper and lower empirical value of gait cycle.
The magnitude constraint for an effective single step is:
wherein ,Aexp Represents the minimum threshold of acceleration peak value, A D Representing the maximum threshold of the peak-to-valley difference.
The non-advancing motion mode of pedestrians comprises actions such as squatting, in-situ jumping and the like, the amplitude is large, the regularity is strong, the characteristics such as the period, the peak value size and the peak value symmetry of the original inertial data waveform are easy to confuse with the advancing motion mode, therefore, pitch angle constraint and two-dimensional acceleration constraint are introduced on the basis of multi-condition amplitude-frequency detection in the zero crossing interval, and the interference of the non-advancing motion mode is eliminated, and particularly the steps (5) and (6) are realized.
(5) Pitch angle constraint
To exclude the effect of the squat-in-place action, pitch angle constraints are introduced. Record t And (3) calculating a pitch angle by using the acquired angular velocity at the moment t, wherein the pitch angle constraint is as follows:
wherein, pitch init Is the initial pitch angle of the human body when standing t ) min For pitch angle pitch t At the position ofMinimum value of interval D exp Is an empirical threshold. If the zero crossing interval meets the multi-condition amplitude-frequency constraint and pitch angle constraint at the same time, the pedestrian is in the in-situ squatting state, and an effective single step is not included.
(6) Two-dimensional acceleration constraint
To exclude the effects of jump-in-place actions, two-dimensional acceleration constraints are introduced. Record a xt If the forward acceleration of the pedestrian at the moment t is the forward acceleration of the pedestrian, the two-dimensional acceleration constraint is as follows:
wherein , and />Respectively-> and />In section->Maximum value of M exp1 and Mexp2 Is an empirical threshold. If the zero crossing interval meets the multi-condition amplitude-frequency constraint and the two-dimensional acceleration constraint at the same time, the pedestrian is in the in-situ jump state, and an effective single step is not included.
(7) Single step detection interval update
The method for updating the zero crossing interval detected by a single step by utilizing a dynamic sliding window method is divided into two cases of including an effective single step and not including an effective single step:
if it isThe inertia data in the interval meets the time-frequency constraint and the amplitude constraint, but does not meet the pitch angle constraint and the two-dimensional acceleration constraint, and shows that the pedestrian is in a travelling motion state, the interval comprises an effective single step, the adjacent wave peak points are divided into one single step, and the next detection interval is updated as->
If it isThe inertia data in the interval does not meet the time-frequency constraint or the amplitude constraint, or meets the pitch angle constraint or the two-dimensional acceleration constraint on the basis of meeting the amplitude-frequency constraint, so that the pedestrian is in a non-advancing motion state, the interval does not contain an effective single step, and the next detection interval is updated as follows>
Repeating the steps (2) - (6) after updating the detection interval, and the like to realize single-step division.
In order to eliminate the interference of various non-travelling motion modes, the invention provides a zero-crossing interval multi-condition amplitude-frequency detection method based on two conditions of time-frequency constraint and amplitude constraint, and simultaneously combines pitch angle constraint and two-dimensional acceleration constraint to distinguish confusable non-travelling motions, thereby further improving single-step division precision. The pedestrian single-step dividing method provided by the invention greatly improves the dead reckoning precision of the pedestrian in the complex motion state.
Features that are described and/or illustrated above with respect to one embodiment may be used in the same way or in a similar way in one or more other embodiments and/or in combination with or instead of the features of the other embodiments.
It should be emphasized that the term "comprises/comprising" when used herein is taken to specify the presence of stated features, integers, steps or components but does not preclude the presence or addition of one or more other features, integers, steps, components or groups thereof.
The many features and advantages of the embodiments are apparent from the detailed specification, and thus, it is intended by the appended claims to cover all such features and advantages of the embodiments which fall within the true spirit and scope thereof. Further, since numerous modifications and changes will readily occur to those skilled in the art, it is not desired to limit the embodiments of the invention to the exact construction and operation illustrated and described, and accordingly, all suitable modifications and equivalents may be resorted to, falling within the scope thereof.
The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
The invention is not described in detail in a manner known to those skilled in the art.
Claims (7)
1. A pedestrian single-step dividing method under a complex motion state is characterized by comprising the following steps of
Collecting acceleration and angular velocity data in various traveling states and non-traveling states;
calculating vertical acceleration to perform zero crossing detection, and extracting a wave peak value and a wave trough value of the acceleration based on a zero crossing point;
establishing time-frequency constraint based on an empirical value of a gait cycle, establishing amplitude constraint based on a minimum threshold of an acceleration peak value, and judging whether the time difference between acceleration peak and valley and the acceleration amplitude meet two constraint conditions or not;
the time-frequency constraint is that
wherein ,ThUpper part 、Th Lower part(s) Is the upper and lower empirical value of the gait cycle,the time points correspond to the acceleration peak value or the acceleration valley value in the two adjacent zero crossing intervals respectively;
the amplitude constraint is that
wherein ,Aexp Represents the minimum threshold of acceleration peak value, A D Representing the maximum threshold for the peak-to-valley difference,respectively the peak value or the valley value of acceleration in two adjacent zero crossing intervals; i A t | max Representing the maximum value of the absolute value of the acceleration in the zero crossing point interval;
establishing pitch angle constraint based on an empirical value of pitch angle change in the squatting process, calculating the pitch angle according to the angular speed data, and judging whether the pitch angle meets constraint conditions or not;
the pitch angle is constrained to
Wherein, pitch init Is the initial pitch angle when the human body stands t Pitch angle (pitch) calculated for time t using the acquired angular velocity t ) min For pitch angle pitch t At the position ofMinimum value of interval D exp Is an empirical threshold;the starting and ending moments of two adjacent zero crossing intervals including wave crests and wave troughs are represented;
establishing two-dimensional acceleration constraint based on an empirical value of acceleration change in the jumping process, calculating forward and vertical accelerations, and judging whether the accelerations in the two directions meet constraint conditions or not;
the two-dimensional acceleration constraint is that
wherein ,for the forward acceleration of the pedestrian at time t, +.> and />Respectively-> and />In section->Maximum value of M exp1 and Mexp2 Is an empirical threshold;
judging whether two adjacent zero-crossing intervals containing wave crests and wave troughs contain an effective single step or not according to the constraint conditions and dividing the effective single step;
the method for judging whether the two adjacent zero crossing intervals containing the wave crest and the wave trough contain an effective single step or not comprises the following steps of: if the acquired data in two adjacent intervals meet the time-frequency constraint and the amplitude constraint, but do not meet the pitch angle constraint and the two-dimensional acceleration constraint, the two-phase zero-crossing intervals comprise effective single steps.
2. The method for single-step division of pedestrians in complex motion states according to claim 1, further comprising updating the single-step detection interval by a dynamic sliding window method.
3. The method for dividing pedestrians in a complex motion state by one step according to claim 2, wherein the method for judging whether the two adjacent zero crossing intervals including the wave crest and the wave trough include an effective single step or not further comprises: if the acquired data in the two adjacent intervals does not meet at least one of time-frequency constraint and amplitude constraint or meet at least one of pitch angle constraint and two-dimensional acceleration constraint, the two adjacent intervals do not contain an effective single step.
4. The method of claim 1, wherein the traveling motion comprises walking or running, and the non-traveling motion comprises shaking, turning in place, squatting, jumping in place.
5. The method for dividing pedestrians in complex motion states in a single step according to claim 1, wherein the zero crossing detection method specifically comprises the following steps of
Calculating the vertical acceleration at the moment t as
wherein ,the vertical acceleration acquired at the moment t is the local standard gravity acceleration g;
when the following condition is satisfied:
A t-T A T ≤0
record A t Is thatI.e. zero crossing, corresponding moment +.>For the zero crossing time, the zero crossing points are calculated in turn> Corresponding zero crossing time->T is the sampling period.
6. The method for dividing pedestrians in complex motion states according to claim 5, wherein the method for extracting the peak value and the trough value of the acceleration comprises
Find outPeak value +.>And (2) the valley value>At the corresponding time
wherein ,|At | max Represents the maximum value of the absolute value of the acceleration in the zero crossing point interval S 1 、S 2 Respectively positive and negative signs.
7. The method for single-step pedestrian classification in complex motion state according to claim 1, characterized in that ifThe interval comprises effective single steps, the adjacent wave peak points are divided into one single step, and the next detection interval is updated to +.>If->The interval does not contain an effective single step, and the next detection interval is updated to +.>
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